Intergenerational change and familial aggregation of body mass index

The relationship between parental BMI and that of their adult offspring, when increased adiposity can become a clinical issue, is unknown. We investigated the intergenerational change in body mass index (BMI) distribution, and examined the sex-specific relationship between parental and adult offspring BMI. Intergenerational change in the distribution of adjusted BMI in 1,443 complete families (both parents and at least one offspring) with 2,286 offspring (1,263 daughters and 1,023 sons) from the west of Scotland, UK, was investigated using quantile regression. Familial correlations were estimated from linear mixed effects regression models. The distribution of BMI showed little intergenerational change in the normal range (\25 kg/m2), decreasing overweightness (25– \30 kg/m2) and increasing obesity (C30 kg/m2). Median BMI was static across generations in males and decreased in females by 0.4 (95% CI: 0.0, 0.7) kg/m2; the 95th percentileincreased by 2.2 (1.1, 3.2) kg/m2 in males and 2.7 (1.4, 3.9) kg/m2 in females. Mothers’ BMI was more strongly associated with daughters’ BMI than was fathers’ (correlation coefficient (95% CI): mothers 0.31 (0.27, 0.36), fathers 0.19 (0.14, 0.25); P = 0.001). Mothers’ and fathers’ BMI were equally correlated with sons’ BMI (correlation coefficient: mothers 0.28 (0.22, 0.33), fathers 0.27 (0.22, 0.33). The increase in BMI between generations was concentrated at the upper end of the distribution. This, alongside the strong parent-offspring correlation, suggests that the increase in BMI is disproportionally greater among offspring of heavier parents. Familial influences on BMI among middle-aged women appear significantly stronger from mothers than father

Loneliness, social support and cardiovascular reactivity to laboratory stress

Self-reported or explicit loneliness and social support have been inconsistently associated with cardiovascular reactivity (CVR) to stress. The present study aimed to adapt an implicit measure of loneliness, and use it alongside the measures of explicit loneliness and social support, to investigate their correlations with CVR to laboratory stress. Twenty-five female volunteers aged between 18 and 39 years completed self-reported measures of loneliness and social support, and an Implicit Association Test (IAT) of loneliness. The systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) reactivity indices were measured in response to psychosocial stress induced in the laboratory. Functional support indices of social support were significantly correlated with CVR reactivity to stress. Interestingly, implicit, but not explicit, loneliness was significantly correlated with DBP reactivity after one of the stressors. No associations were found between structural support and CVR indices. Results are discussed in terms of validity of implicit versus explicit measures and possible factors that affect physiological outcomes

Individuals with Fear of Blushing Explicitly and Automatically Associate Blushing with Social Costs

To explain fear of blushing, it has been proposed that individuals with fear of blushing overestimate the social costs of their blushing. Current information-processing models emphasize the relevance of differentiating between more automatic and more explicit cognitions, as both types of cognitions may independently influence behavior. The present study tested whether individuals with fear of blushing expect blushing to have more negative social consequences than controls, both on an explicit level and on a more automatic level. Automatic associations between blushing and social costs were assessed in a treatment-seeking sample of individuals with fear of blushing who met DSM-IV criteria for social anxiety disorder (n = 49) and a non-anxious control group (n = 27) using a single-target Implicit Association Test (stIAT). In addition, participants’ explicit expectations about the social costs of their blushing were assessed. Individuals with fear of blushing showed stronger associations between blushing and negative outcomes, as indicated by both stIAT and self-report. The findings support the view that automatic and explicit associations between blushing and social costs may both help to enhance our understanding of the cognitive processes that underlie fear of blushing

Exploring the Role of Explicit and Implicit Self-Esteem and Self-Compassion in Anxious and Depressive Symptomatology Following Acquired Brain Injury

[EN] Objectives Acquired brain injury (ABI) can lead to the emergence of several disabilities and is commonly associated with high rates of anxiety and depression symptoms. Self-related constructs, such as self-esteem and self-compassion, might play a key role in this distressing symptomatology. Low explicit (i.e., deliberate) self-esteem is associated with anxiety and depression after ABI. However, implicit (i.e., automatic) self-esteem, explicit-implicit self-discrepancies, and self-compassion could also significantly contribute to this symptomatology. The purpose of the present study was to examine whether implicit self-esteem, explicit-implicit self-discrepancy (size and direction), and self-compassion are related to anxious and depressive symptoms after ABI in adults, beyond the contribution of explicit self-esteem. Methods The sample consisted 38 individuals with ABI who were enrolled in a long-term rehabilitation program. All participants completed the measures of explicit self-esteem, implicit self-esteem, self-compassion, anxiety, and depression. Pearson's correlations and hierarchical regression models were calculated. Results Findings showed that both self-compassion and implicit self-esteem negatively accounted for unique variance in anxiety and depression when controlling for explicit self-esteem. Neither the size nor direction of explicit-implicit self-discrepancy was significantly associated with anxious or depressive symptomatology. Conclusions The findings suggest that the consideration of self-compassion and implicit self-esteem, in addition to explicit self-esteem, contributes to understanding anxiety and depression following ABI.Lorena Desdentado is supported by a FPU doctoral scholarship (FPU18/01690) from the Spanish Ministry of Universities. This work was supported by CIBEROBN, an initiative of the ISCIII (ISC III CB06 03/0052).Desdentado, L.; Cebolla, A.; Miragall, M.; Llorens Rodríguez, R.; Navarro, MD.; Baños, RM. (2021). Exploring the Role of Explicit and Implicit Self-Esteem and Self-Compassion in Anxious and Depressive Symptomatology Following Acquired Brain Injury. Mindfulness. 12(4):899-910. https://doi.org/10.1007/s12671-020-01553-wS899910124Anson, K., & Ponsford, J. (2006). Coping and emotional adjustment following traumatic brain injury. The Journal of Head Trauma Rehabilitation, 21(3), 248–259. https://doi.org/10.1097/00001199-200605000-00005.Baños, R. M., & Guillén, V. (2000). Psychometric characteristics in normal and social phobic samples for a Spanish version of the Rosenberg Self-Esteem Scale. Psychological Reports, 87(1), 269–274. https://doi.org/10.2466/pr0.2000.87.1.269.Beadle, E. J., Ownsworth, T., Fleming, J., & Shum, D. (2016). The impact of traumatic brain injury on self-identity: a systematic review of the evidence for self-concept changes. The Journal of Head Trauma Rehabilitation, 31(2), E12–E25. https://doi.org/10.1097/HTR.0000000000000158.Beck, A. T. (1979). Cognitive therapy of depression. New York: Guilford Press.Beevers, C. G. (2005). Cognitive vulnerability to depression: A dual process model. Clinical Psychology Review, 25(7), 975–1002. https://doi.org/10.1016/j.cpr.2005.03.003.Bos, A. E. R., Huijding, J., Muris, P., Vogel, L. R. R., & Biesheuvel, J. (2010). Global, contingent and implicit self-esteem and psychopathological symptoms in adolescents. Personality and Individual Differences, 48(3), 311–316. https://doi.org/10.1016/j.paid.2009.10.025.Bowerman, B. L., & O’Connell, R. T. (1990). Linear statistical models: An applied approach (2nd ed.). Belmont, CA: Duxbury.Brenner, R. E., Heath, P. J., Vogel, D. L., & Credé, M. (2017). Two is more valid than one: examining the factor structure of the self-compassion scale (SCS). Journal of Counseling Psychology, 64(6), 696–707. https://doi.org/10.1037/cou0000211.Brysbaert, M. (2019). How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables. Journal of Cognition, 2(1), 1–38. https://doi.org/10.5334/joc.72.Carroll, E., & Coetzer, R. (2011). Identity, grief and self-awareness after traumatic brain injury. Neuropsychological Rehabilitation, 21(3), 289–305. https://doi.org/10.1080/09602011.2011.555972.Corrigan, P. W., & Watson, A. C. (2002). The paradox of self-stigma and mental illness. Clinical Psychology: Science and Practice, 9(1), 35–53. https://doi.org/10.1093/clipsy/9.1.35.Creemers, D. H. M., Scholte, R. H. J., Engels, R. C. M. E., Prinstein, M. J., & Wiers, R. W. (2012). Implicit and explicit self-esteem as concurrent predictors of suicidal ideation, depressive symptoms, and loneliness. Journal of Behavior Therapy and Experimental Psychiatry, 43(1), 638–646. https://doi.org/10.1016/j.jbtep.2011.09.006.Creemers, D. H. M., Scholt, R. H. J., Engels, R. C. M. E., Prinstein, M. J., & Wiers, R. W. (2013). Damaged self-esteem is associated with internalizing problems. Frontiers in Psychology, 4, 152. https://doi.org/10.3389/fpsyg.2013.00152.Curvis, W., Simpson, J., & Hampson, N. (2018). Factors associated with self-esteem following acquired brain injury in adults: a systematic review. Neuropsychological Rehabilitation, 28(1), 142–183. https://doi.org/10.1080/09602011.2016.1144515.Elbaum, J., & Benson, D. (Eds.). (2007). Acquired brain injury: an integrative neuro-rehabilitation approach. New York: Springer. https://doi.org/10.1007/978-0-387-37575-5.Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149.FEDACE. (2015). Las personas con daño cerebral adquirido en España. Ministerio de Sanidad, Servicios Sociales e Igualdad. Retrieved May 21, 2020, from: https://fedace.org/index.php?V_dir=MSC&V_mod=download&f=2016-9/26-16-4-11.admin.Informe_FEDACE_RPD_para_DDC-1.pdf.Feigin, V. L., Forouzanfar, M. H., Krishnamurthi, R., Mensah, G. A., Connor, M., Bennett, D. A., Moran, A. E., Sacco, R. L., Anderson, L., Truelsen, T., O’Donnell, M., Venketasubramanian, N., Barker-Collo, S., Lawes, C. M. M., Wang, W., Shinohara, Y., Witt, E., Ezzati, M., & Naghavi, M. (2014). Global and regional burden of stroke during 1990-2010: findings from the Global Burden of Disease Study 2010. The Lancet, 383(9913), 245–254. https://doi.org/10.1016/S0140-6736(13)61953-4.Fennell, M. J. V. (1997). Low self-esteem: a cognitive perspective. Behavioural and Cognitive Psychotherapy, 25(1), 1–26. https://doi.org/10.1017/s1352465800015368.Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. https://doi.org/10.1016/0022-3956(75)90026-6.Garcia-Campayo, J., Navarro-Gil, M., Andrés, E., Montero-Marin, J., López-Artal, L., Marcos, M., & Demarzo, P. (2014). Validation of the Spanish versions of the long (26 items) and short (12 items) forms of the Self-Compassion Scale (SCS). Health and Quality of Life Outcomes, 12(4). https://doi.org/10.1186/1477-7525-12-4.GBD 2016 Traumatic Brain Injury and Spinal Cord Injury Collaborators. (2018). Global, regional, and national burden of traumatic brain injury and spinal cord injury, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology, 18(1), 56–87. https://doi.org/10.1016/S1474-4422(18)30415-0.Gould, K. R., Ponsford, J. L., Johnston, L., & Schönberger, M. (2011). Relationship between psychiatric disorders and 1-year psychosocial outcome following traumatic brain injury. The Journal of Head Trauma Rehabilitation, 26(1), 79–89. https://doi.org/10.1097/HTR.0b013e3182036799.Gracey, F., Palmer, S., Rous, B., Psaila, K., Shaw, K., O’Dell, J., Cope, J., & Mohamed, S. (2008). “Feeling part of things”: personal construction of self after brain injury. Neuropsychological Rehabilitation, 18(5–6), 627–650. https://doi.org/10.1080/09602010802041238.Gracey, F., Evans, J. J., & Malley, D. (2009). Capturing process and outcome in complex rehabilitation interventions: a “Y-shaped” model. Neuropsychological Rehabilitation, 19(6), 867–890. https://doi.org/10.1080/09602010903027763.Greenwald, A. G., & Farnham, S. D. (2000). Using the Implicit Association Test to measure self-esteem and self-concept. Journal of Personality and Social Psychology, 79(6), 1022–1038. https://doi.org/10.1037/0022-3514.79.6.1022.Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: the Implicit Association Test. Journal of Personality and Social Psychology, 74(6), 1464–1480. https://doi.org/10.1037/0022-3514.74.6.1464.Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the Implicit Association Test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197–216. https://doi.org/10.1037/0022-3514.85.2.197.Hackett, M. L., Yapa, C., Parag, V., & Anderson, C. S. (2005). Frequency of depression after stroke: a systematic review of observational studies. Stroke, 36(6), 1330–1340. https://doi.org/10.1161/01.STR.0000165928.19135.35.Haeffel, G. J., Abramson, L. Y., Brazy, P. C., Shah, J. Y., Teachman, B. A., & Nosek, B. A. (2007). Explicit and implicit cognition: a preliminary test of a dual-process theory of cognitive vulnerability to depression. Behaviour Research and Therapy, 45(6), 1155–1167. https://doi.org/10.1016/j.brat.2006.09.003.Ingram, R. E. (1984). Toward an information-processing analysis of depression. Cognitive Therapy and Research, 8(5), 443–477. https://doi.org/10.1007/BF01173284.Izuma, K., Kennedy, K., Fitzjohn, A., Sedikides, C., & Shibata, K. (2018). Neural activity in the reward-related brain regions predicts implicit self-esteem: a novel validity test of psychological measures using neuroimaging. Journal of Personality and Social Psychology, 114(3), 343–357. https://doi.org/10.1037/pspa0000114.Khan-Bourne, N., & Brown, R. G. (2003). Cognitive behaviour therapy for the treatment of depression in individuals with brain injury. Neuropsychological Rehabilitation, 13(1–2), 89–107. https://doi.org/10.1080/09602010244000318.Kim, H. S., & Moore, M. T. (2019). Symptoms of depression and the discrepancy between implicit and explicit self-esteem. Journal of Behavior Therapy and Experimental Psychiatry, 63, 1–5. https://doi.org/10.1016/j.jbtep.2018.12.001.Lane, K. A., Banaji, M. R., Nosek, B. A., & Greenwald, A. G. (2007). Understanding and using the Implicit Association Test: IV. What we know (so far) about the method. In B. Wittenbrink & N. Schwarz (Eds.), Implicit measures of attitudes (pp. 59–102). New York: The Guildford Press.Leary, M. R., Tate, E. B., Adams, C. E., Batts Allen, A., & Hancock, J. (2007). Self-compassion and reactions to unpleasant self-relevant events: the implications of treating oneself kindly. Personality Processes and Individual Differences, 92(5), 887–904. https://doi.org/10.1037/0022-3514.92.5.887.Lennon, A., Bramham, J., Carroll, À., McElligott, J., Carton, S., Waldron, B., Fortune, D., Burke, T., Fitzhenry, M., & Benson, C. (2014). A qualitative exploration of how individuals reconstruct their sense of self following acquired brain injury in comparison with spinal cord injury. Brain Injury, 28(1), 27–37. https://doi.org/10.3109/02699052.2013.848378.Longworth, C., Deakins, J., Rose, D., & Gracey, F. (2018). The nature of self-esteem and its relationship to anxiety and depression in adult acquired brain injury. Neuropsychological Rehabilitation, 28(7), 1078–1094. https://doi.org/10.1080/09602011.2016.1226185.MacBeth, A., & Gumley, A. (2012). Exploring compassion: a meta-analysis of the association between self-compassion and psychopathology. Clinical Psychology Review, 32(6), 545–552. https://doi.org/10.1016/j.cpr.2012.06.003.McDonald, S., Saad, A., & James, C. (2011). Social dysdecorum following severe traumatic brain injury: loss of implicit social knowledge or loss of control? Journal of Clinical and Experimental Neuropsychology, 33(6), 619–630. https://doi.org/10.1080/13803395.2011.553586.Milne, E., & Grafman, J. (2001). Ventromedial prefrontal cortex lesions in humans eliminate implicit gender stereotyping. The Journal of Neuroscience, 21(12), 1–6.Moors, A., & De Houwer, J. (2006). Automaticity: a theoretical and conceptual analysis. Psychological Bulletin, 132(2), 297–326. https://doi.org/10.1037/0033-2909.132.2.297.Muris, P., & Petrocchi, N. (2017). Protection or vulnerability? A meta-analysis of the relations between the positive and negative components of self-compassion and psychopathology. Clinical Psychology & Psychotherapy, 24(2), 373–383. https://doi.org/10.1002/cpp.2005.Myers, R. (2000). Classical and modern regression with applications (2nd ed.). Belmont, CA: Duxbury.Neff, K. D. (2003). Self-compassion: an alternative conceptualization of a healthy attitude toward oneself. Self and Identity, 2(2), 85–101. https://doi.org/10.1080/15298860309032.Neff, K. D., & Vonk, R. (2009). Self-compassion versus global self-esteem: two different ways of relating to oneself. Journal of Personality, 77, 23–50. https://doi.org/10.1111/j.1467-6494.2008.00537.x.Neff, K. D., Tóth-Király, I., Yarnell, L. M., Arimitsu, K., Castilho, P., Ghorbani, N., Guo, H. X., Hirsch, J. K., Hupfeld, J., Hutz, C. S., Kotsou, I., Lee, W. K., Montero-Marin, J., Sirois, F. M., De Souza, L. K., Svendsen, J. L., Wilkinson, R. B., & Mantzios, M. (2019). Examining the factor structure of the Self-Compassion Scale in 20 diverse samples: support for use of a total score and six subscale scores. Psychological Assessment, 31(1), 27–45. https://doi.org/10.1037/pas0000629.Norton, P. J., & Paulus, D. J. (2017). Transdiagnostic models of anxiety disorder: theoretical and empirical underpinnings. Clinical Psychology Review, 56, 122–137. https://doi.org/10.1016/j.cpr.2017.03.004.Nosek, B. A., & Banaji, M. R. (2001). The go/no-go association task. Social Cognition, 19(6), 625–664. https://doi.org/10.1521/soco.19.6.625.20886.Oddy, M., & Herbert, C. (2003). Intervention with families following brain injury: evidence-based practice. Neuropsychological Rehabilitation, 13(1–2), 259–273. https://doi.org/10.1080/09602010244000345.Ouimet, A. J., Gawronski, B., & Dozois, D. J. A. (2009). Cognitive vulnerability to anxiety: a review and an integrative model. Clinical Psychology Review, 29(6), 459–470. https://doi.org/10.1016/j.cpr.2009.05.004.Ponsford, J., Kelly, A., & Couchman, G. (2014). Self-concept and self-esteem after acquired brain injury: a control group comparison. Brain Injury, 28(2), 146–154. https://doi.org/10.3109/02699052.2013.859733.Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the Self-Compassion Scale. Clinical Psychology & Psychotherapy, 18(3), 250–255. https://doi.org/10.1002/cpp.702.Romero, M., Sánchez, A., Marín, C., Navarro, M. D., Ferri, J., & Noé, E. (2012). Clinical usefulness of the Spanish version of the Mississippi Aphasia Screening Test (MASTsp): validation in stroke patients. Neurología (English Edition), 27(4), 216–224. https://doi.org/10.1016/j.nrleng.2011.06.001.Rosenberg, M. (1965). Rosenberg Self-Esteem Scale (RSE). Acceptance and Commitment Therapy. Measures Package, 61, 52 /S0034-98872009000600009.Sandstrom, M. J., & Jordan, R. (2008). Defensive self-esteem and aggression in childhood. Journal of Research in Personality, 42(2), 506–514. https://doi.org/10.1016/j.jrp.2007.07.008.Schönberger, M., & Ponsford, J. (2010). The factor structure of the Hospital Anxiety and Depression Scale in individuals with traumatic brain injury. Psychiatry Research, 179(3), 342–349. https://doi.org/10.1016/j.psychres.2009.07.003.Schröder-Abé, M., Rudolph, A., & Schütz, A. (2007). High implicit self-esteem is not necessarily advantageous: discrepancies between explicit and implicit self-esteem and their relationship with anger expression and psychological health. European Journal of Personality, 21(3), 319–339. https://doi.org/10.1002/per.626.Scoglio, A. A. J., Rudat, D. A., Garvert, D., Jarmolowski, M., Jackson, C., & Herman, J. L. (2018). Self-compassion and responses to trauma: the role of emotion regulation. Journal of Interpersonal Violence, 33(13), 2016–2036. https://doi.org/10.1177/0886260515622296.Sloan, E., Hall, K., Moulding, R., Bryce, S., Mildred, H., & Staiger, P. K. (2017). Emotion regulation as a transdiagnostic treatment construct across anxiety, depression, substance, eating and borderline personality disorders: a systematic review. Clinical Psychology Review, 57, 141–163. https://doi.org/10.1016/j.cpr.2017.09.002.Smeijers, D., Vrijsen, J. N., van Oostrom, I., Isaac, L., Speckens, A., Becker, E. S., & Rinck, M. (2017). Implicit and explicit self-esteem in remitted depressed patients. Journal of Behavior Therapy and Experimental Psychiatry, 54, 301–306. https://doi.org/10.1016/j.jbtep.2016.10.006.Smith, E. R., & DeCoster, J. (2000). Dual-process models in social and cognitive psychology: conceptual integration and links to underlying memory systems. Personality and Social Psychology Review, 4(2), 108–131. https://doi.org/10.1207/S15327957PSPR0402_01.Sowislo, J. F., & Orth, U. (2013). Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies. Psychological Bulletin, 139(1), 213–240. https://doi.org/10.1037/a0028931.Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8(3), 220–247. https://doi.org/10.1207/s15327957pspr0803_1.Terol-Cantero, M. C., Cabrera-Perona, V., & Martín-Aragón, M. (2015). Hospital Anxiety and Depression Scale (HADS) review in Spanish samples. Anales de Psicología, 31(2), 494–503. https://doi.org/10.6018/analesps.31.2.172701.Tóth-Király, I., & Neff, K. D. (2020). Is self-compassion universal? Support for the measurement invariance of the Self-Compassion Scale across populations. Assessment. Advance online publication. https://doi.org/10.1177/1073191120926232.Turner-Stokes, L., & Wade, D. (2003). Rehabilitation following acquired brain injury: National Clinical Guidelines. Clinical Medicine, 4(1), 61–65. https://doi.org/10.7861/clinmedicine.4-1-61.Tyerman, A., & Humphrey, M. (1984). Changes in self-concept following severe head injury. International Journal of Rehabilitation Research, 7(1), 11–23. https://doi.org/10.1097/00004356-198403000-00002.Valiente, C., Cantero, D., Vázquez, C., Sanchez, Á., Provencio, M., & Espinosa, R. (2011). Implicit and explicit self-esteem discrepancies in paranoia and depression. Journal of Abnormal Psychology, 120(3), 691–699. https://doi.org/10.1037/a0022856.Vickery, C. D., Sepehri, A., & Evans, C. C. (2008). Self-esteem in an acute stroke rehabilitation sample: a control group comparison. Clinical Rehabilitation, 22(2), 179–187. https://doi.org/10.1177/0269215507080142.Whelan-Goodinson, R., Ponsford, J., & Schönberger, M. (2009). Validity of the Hospital Anxiety and Depression Scale to assess depression and anxiety following traumatic brain injury as compared with the Structured Clinical Interview for DSM-IV. Journal of Affective Disorders, 114(1–3), 94–102. https://doi.org/10.1016/j.jad.2008.06.007.Zeigler-Hill, V. (2006). Discrepancies between implicit and explicit self-esteem: Implications for narcissism and self-esteem instability. Journal of Personality, 74(1), 119–144. https://doi.org/10.1111/j.1467-6494.2005.00371.x.Zessin, U., Dickhäuser, O., & Garbade, S. (2015). The relationship between self-compassion and well-being: a meta-analysis. Applied Psychology. Health and Well-Being, 7(3), 340–364. https://doi.org/10.1111/aphw.12051.Zhang, J. W., Chen, S., & Tomova Shakur, T. K. (2020). From me to you: Self-compassion predicts acceptance of own and others’ imperfections. Personality and Social Psychology Bulletin, 46(2), 228–242. https://doi.org/10.1177/0146167219853846.Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67(6), 361–370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x

Whole-genome cancer analysis as an approach to deeper understanding of tumour biology

Recent advances in DNA sequencing technology are providing unprecedented opportunities for comprehensive analysis of cancer genomes, exomes, transcriptomes, as well as epigenomic components. The integration of these data sets with well-annotated phenotypic and clinical data will expedite improved interventions based on the individual genomics of the patient and the specific disease

Maternal smoking during pregnancy and subcutaneous fat mass in early childhood. The Generation R Study

Maternal smoking during pregnancy increases the risk of obesity in the offspring. Not much is known about the associations with other measures of body composition. We assessed the associations of maternal smoking during pregnancy with the development of subcutaneous fat mass measured as peripheral and central skinfold thickness measurements in early childhood, in a population-based prospective cohort study from early fetal life onward in the city of Rotterdam, The Netherlands. The study was performed in 907 mothers and their children at the ages of 1.5, 6 and 24 months. As compared to non-smoking mothers, mothers who continued smoking during pregnancy were more likely to have a younger age and a lower educational level. Their children had a lower birth weight, higher risk of small size for gestational age and were breastfed for a shorter duration (P-values <0.01). We did not observe differences in peripheral, central and total subcutaneous fat mass between the offspring of non-smoking mothers, mothers who smoked in first trimester only and mothers who continued smoking during pregnancy (P > 0.05). Also, the reported number of cigarettes smoked by mothers in both first and third trimester of pregnancy were not associated with peripheral, central and total subcutaneous fat mass in the offspring at the ages of 1.5, 6 and 24 months. Our findings suggest that fetal exposure to cigarette smoke during pregnancy does not influence subcutaneous fat mass in early childhood. Follow-up studies are needed in children at older ages and to identify associations of maternal smoking during pregnancy with other measures of body composition

Mutational Profiling of Kinases in Human Tumours of Pancreatic Origin Identifies Candidate Cancer Genes in Ductal and Ampulla of Vater Carcinomas

BACKGROUND: Protein kinases are key regulators of cellular processes (such as proliferation, apoptosis and invasion) that are often deregulated in human cancers. Accordingly, kinase genes have been the first to be systematically analyzed in human tumors leading to the discovery that many oncogenes correspond to mutated kinases. In most cases the genetic alterations translate in constitutively active kinase proteins, which are amenable of therapeutic targeting. Tumours of the pancreas are aggressive neoplasms for which no effective therapeutic strategy is currently available. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a DNA-sequence analysis of a selected set of 35 kinase genes in a panel of 52 pancreatic exocrine neoplasms, including 36 pancreatic ductal adenocarcinoma, and 16 ampulla of Vater cancer. Among other changes we found somatic mutations in ATM, EGFR, EPHA3, EPHB2, and KIT, none of which was previously described in cancers. CONCLUSIONS/SIGNIFICANCE: Although the alterations identified require further experimental evaluation, the localization within defined protein domains indicates functional relevance for most of them. Some of the mutated genes, including the tyrosine kinases EPHA3 and EPHB2, are clearly amenable to pharmacological intervention and could represent novel therapeutic targets for these incurable cancers

Diabetes susceptibility in ethnic minority groups from Turkey, Vietnam, Sri Lanka and Pakistan compared with Norwegians - the association with adiposity is strongest for ethnic minority women

<p>Abstract</p> <p>Background</p> <p>The difference in diabetes susceptibility by ethnic background is poorly understood. The aim of this study was to assess the association between adiposity and diabetes in four ethnic minority groups compared with Norwegians, and take into account confounding by socioeconomic position.</p> <p>Methods</p> <p>Data from questionnaires, physical examinations and serum samples were analysed for 30-to 60-year-olds from population-based cross-sectional surveys of Norwegians and four immigrant groups, comprising 4110 subjects born in Norway (n = 1871), Turkey (n = 387), Vietnam (n = 553), Sri Lanka (n = 879) and Pakistan (n = 420). Known and screening-detected diabetes cases were identified. The adiposity measures BMI, waist circumference and waist-hip ratio (WHR) were categorized into levels of adiposity. Gender-specific logistic regression models were applied to estimate the risk of diabetes for the ethnic minority groups adjusted for adiposity and income-generating work, years of education and body height used as a proxy for childhood socioeconomic position.</p> <p>Results</p> <p>The age standardized diabetes prevalence differed significantly between the ethnic groups (women/men): Pakistan: 26.4% (95% CI 20.1-32.7)/20.0% (14.9-25.2); Sri Lanka: 22.5% (18.1-26.9)/20.7% (17.3-24.2), Turkey: 11.9% (7.2-16.7)/12.0% (7.6-16.4), Vietnam: 8.1% (5.1-11.2)/10.4% (6.6-14.1) and Norway: 2.7% (1.8-3.7)/6.4% (4.6-8.1). The prevalence increased more in the minority groups than in Norwegians with increasing levels of BMI, WHR and waist circumference, and most for women. Highly significant ethnic differences in the age-standardized prevalence of diabetes were found for both genders in all categories of all adiposity measures (<it>p </it>< 0.001). The Odds Ratio (OR) for diabetes adjusted for age, WHR, body height, education and income-generating work with Norwegians as reference was 2.9 (1.30-6.36) for Turkish, 2.7 (1.29-5.76) for Vietnamese, 8.0 (4.19-15.14) for Sri Lankan and 8.3 (4.37-15.58) for Pakistani women. Men from Sri Lanka and Pakistan had identical ORs (3.0 (1.80-5.12)).</p> <p>Conclusions</p> <p>A high prevalence of diabetes was found in 30-to 60-year-olds from ethnic minority groups in Oslo, with those from Sri Lanka and Pakistan at highest risk. For all levels of adiposity, a higher susceptibility for diabetes was observed for ethnic minority groups compared with Norwegians. The association persisted after adjustment for socioeconomic position for all minority women and for men from Sri Lanka and Pakistan.</p

Panax ginseng Modulates Cytokines in Bone Marrow Toxicity and Myelopoiesis: Ginsenoside Rg1 Partially Supports Myelopoiesis

In this study, we have demonstrated that Korean Panax ginseng (KG) significantly enhances myelopoiesis in vitro and reconstitutes bone marrow after 5-flurouracil-induced (5FU) myelosuppression in mice. KG promoted total white blood cell, lymphocyte, neutrophil and platelet counts and improved body weight, spleen weight, and thymus weight. The number of CFU-GM in bone marrow cells of mice and serum levels of IL-3 and GM-CSF were significantly improved after KG treatment. KG induced significant c-Kit, SCF and IL-1 mRNA expression in spleen. Moreover, treatment with KG led to marked improvements in 5FU-induced histopathological changes in bone marrow and spleen, and partial suppression of thymus damage. The levels of IL-3 and GM-CSF in cultured bone marrow cells after 24 h stimulation with KG were considerably increased. The mechanism underlying promotion of myelopoiesis by KG was assessed by monitoring gene expression at two time-points of 4 and 8 h. Treatment with Rg1 (0.5, 1 and 1.5 µmol) specifically enhanced c-Kit, IL-6 and TNF-α mRNA expression in cultured bone marrow cells. Our results collectively suggest that the anti-myelotoxicity activity and promotion of myelopoiesis by KG are mediated through cytokines. Moreover, the ginsenoside, Rg1, supports the role of KG in myelopoiesis to some extent

The Servant Leadership Survey: Development and Validation of a Multidimensional Measure

Purpose: The purpose of this paper is to describe the development and validation of a multi-dimensional instrument to measure servant leadership. Design/Methodology/Approach Based on an extensive literature review and expert judgment, 99 items were formulated. In three steps, using eight samples totaling 1571 persons from The Netherlands and the UK with a diverse occupational background, a combined exploratory and confirmatory factor analysis approach was used. This was followed by an analysis of the criterion-related validity. Findings: The final result is an eight-dimensional measure of 30 items: the eight dimensions being: standing back, forgiveness, courage, empowerment, accountability, authenticity, humility, and stewardship. The internal consistency of the subscales is good. The results show that the Servant Leadership Survey (SLS) has convergent validity with other leadership measures, and also adds unique elements to the leadership field. Evidence for criterion-related validity came from studies relating the eight dimensions to well-being and performance. Implications: With this survey, a valid and reliable instrument to measure the essential elements of servant leadership has been introduced. Originality/Value The SLS is the first measure where the underlying factor structure was developed and confirmed across several field studies in two countries. It can be used in future studies to test the underlying premises of servant leadership theory. The SLS provides a clear picture of the key servant leadership qualities and shows where improvements can be made on the individual and organizational level; as such, it may also offer a valuable starting point for training and leadership development