166 research outputs found

    Measurements of the reaction pˉpϕη\bar{p}p \to \phi \eta of antiproton annihilation at rest at three hydrogen target densities

    Full text link
    The proton-antiproton annihilation at rest into the ϕη\phi\eta final state was measured for three different target densities: liquid hydrogen, gaseous hydrogen at NTP and at a low pressure of 5 mbar. The yield of this reaction in the liquid hydrogen target is smaller than in the low-pressure gas target. The branching ratios of the ϕη\phi\eta channel were calculated on the basis of simultaneous analysis of the three data samples. The branching ratio for annihilation into ϕη\phi\eta from the 3S1^3S_1 protonium state turns out to be about ten times smaller as compared to the one from the 1P1^1P_1 state.Comment: 10 pages, 3 Postscript figures. Accepted by Physics Letters

    HIV-1 tat addresses dendritic cells to induce a predominant th1-type adaptive immune response that appears prevalent in the asymptomatic stage of infection

    Get PDF
    Tat is an early regulatory protein that plays a major role in human HIV-1 replication and AIDS pathogenesis, and therefore, it represents a key target for the host immune response. In natural infection, however, Abs against Tat are produced only by a small fraction (∼20%) of asymptomatic individuals and are rarely seen in progressors, suggesting that Tat may possess properties diverting the adaptive immunity from generating humoral responses. Here we show that a Th1-type T cell response against Tat is predominant over a Th2-type B cell response in natural HIV-1 infection. This is likely due to the capability of Tat to selectively target and very efficiently enter CD1a-expressing monocyte-derived dendritic cells (MDDC), which represent a primary target for the recognition and response to virus Ag. Upon cellular uptake, Tat induces MDDC maturation and Th1-associated cytokines and β-chemokines production and polarizes the immune response in vitro to the Th1 pattern through the transcriptional activation of TNF-αgene expression. This requires the full conservation of Tat transactivation activity since neither MDDC maturation nor TNF-α production are found with either an oxidized Tat, which does not enter MDDC, or with a Tat protein mutated in the cysteine-rich region (cys22 Tat), which enters MDDC as the wild-type Tat but is transactivation silent. Consistently with these data, inoculation of monkeys with the native wild-type Tat induced a predominant Th1 response, whereas cys22 Tat generated mostly Th2 responses, therefore providing evidence that Tat induces a predominant Th1 polarized adaptive immune response in the host. Copyright © 2009 by The American Association of Immunologists, Inc

    Understanding the implementation of evidence-based care: A structural network approach

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Recent study of complex networks has yielded many new insights into phenomenon such as social networks, the internet, and sexually transmitted infections. The purpose of this analysis is to examine the properties of a network created by the 'co-care' of patients within one region of the Veterans Health Affairs.</p> <p>Methods</p> <p>Data were obtained for all outpatient visits from 1 October 2006 to 30 September 2008 within one large Veterans Integrated Service Network. Types of physician within each clinic were nodes connected by shared patients, with a weighted link representing the number of shared patients between each connected pair. Network metrics calculated included edge weights, node degree, node strength, node coreness, and node betweenness. Log-log plots were used to examine the distribution of these metrics. Sizes of k-core networks were also computed under multiple conditions of node removal.</p> <p>Results</p> <p>There were 4,310,465 encounters by 266,710 shared patients between 722 provider types (nodes) across 41 stations or clinics resulting in 34,390 edges. The number of other nodes to which primary care provider nodes have a connection (172.7) is 42% greater than that of general surgeons and two and one-half times as high as cardiology. The log-log plot of the edge weight distribution appears to be linear in nature, revealing a 'scale-free' characteristic of the network, while the distributions of node degree and node strength are less so. The analysis of the k-core network sizes under increasing removal of primary care nodes shows that about 10 most connected primary care nodes play a critical role in keeping the <it>k</it>-core networks connected, because their removal disintegrates the highest <it>k</it>-core network.</p> <p>Conclusions</p> <p>Delivery of healthcare in a large healthcare system such as that of the US Department of Veterans Affairs (VA) can be represented as a complex network. This network consists of highly connected provider nodes that serve as 'hubs' within the network, and demonstrates some 'scale-free' properties. By using currently available tools to explore its topology, we can explore how the underlying connectivity of such a system affects the behavior of providers, and perhaps leverage that understanding to improve quality and outcomes of care.</p

    Prevention and management of radiotherapy-related toxicities in gynecological malignancies. Position paper on behalf of AIRO (Italian Association of Radiotherapy and Clinical Oncology)

    Get PDF
    Multi-modal therapies for gynecological cancers management may determine a wide range of side effects which depend on therapy-related factors and patient characteristics and comorbidities. Curative or adjuvant pelvic radiotherapy is linked with acute and late toxicity due to irradiation of organs at risk, as small and large bowel, rectum, bladder, pelvic bone, vagina and bone marrow. Successful toxicity management varies with its severity, Radiation Centre practice and experience and skills of radiation oncologists. This position paper was designed by the Italian Association of Radiation and Clinical Oncology Gynecology Study Group to provide radiation oncologists with evidence-based strategies to prevent and manage acute and late toxicities and follow-up recommendations for gynecological cancer patients submitted radiotherapy. Six workgroups of radiation oncologists with over 5 years of experience in gynecologic cancers were setup to investigate radiotherapy-related toxicities. For each topic, PubMed database was searched for relevant English language papers from January 2005 to December 2022. Titles and abstracts of results were checked to verify suitability for the document. Reference lists of selected studies and review papers were added if pertinent. Data on incidence, etiopathogenesis, prevention, treatment and follow-up of acute and late side effects for each organ at risk are presented and discussed

    Evaluation of the 2022 West Nile virus forecasting challenge, USA

    Get PDF
    \ua9 2025. The Author(s). BACKGROUND: West Nile virus (WNV) is the most common cause of mosquito-borne disease in the continental USA, with an average of ~1200 severe, neuroinvasive cases reported annually from 2005 to 2021 (range 386-2873). Despite this burden, efforts to forecast WNV disease to inform public health measures to reduce disease incidence have had limited success. Here, we analyze forecasts submitted to the 2022 WNV Forecasting Challenge, a follow-up to the 2020 WNV Forecasting Challenge. METHODS: Forecasting teams submitted probabilistic forecasts of annual West Nile virus neuroinvasive disease (WNND) cases for each county in the continental USA for the 2022 WNV season. We assessed the skill of team-specific forecasts, baseline forecasts, and an ensemble created from team-specific forecasts. We then characterized the impact of model characteristics and county-specific contextual factors (e.g., population) on forecast skill. RESULTS: Ensemble forecasts for 2022 anticipated a season at or below median long-term WNND incidence for nearly all (&gt; 99%) counties. More counties reported higher case numbers than anticipated by the ensemble forecast median, but national caseload (826) was well below the 10-year median (1386). Forecast skill was highest for the ensemble forecast, though the historical negative binomial baseline model and several team-submitted forecasts had similar forecast skill. Forecasts utilizing regression-based frameworks tended to have more skill than those that did not and models using climate, mosquito surveillance, demographic, or avian data had less skill than those that did not, potentially due to overfitting. County-contextual analysis showed strong relationships with the number of years that WNND had been reported and permutation entropy (historical variability). Evaluations based on weighted interval score and logarithmic scoring metrics produced similar results. CONCLUSIONS: The relative success of the ensemble forecast, the best forecast for 2022, suggests potential gains in community ability to forecast WNV, an improvement from the 2020 Challenge. Similar to the previous challenge, however, our results indicate that skill was still limited with general underprediction despite a relative low incidence year. Potential opportunities for improvement include refining mechanistic approaches, integrating additional data sources, and considering different approaches for areas with and without previous cases

    A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America

    Get PDF
    Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America (U.S.A.). The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infections expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously

    Therapeutic immunization with HIV-1 Tat reduces immune activation and loss of regulatory T-cells and improves immune function in subjects on HAART.

    Get PDF
    Although HAART suppresses HIV replication, it is often unable to restore immune homeostasis. Consequently, non-AIDS-defining diseases are increasingly seen in treated individuals. This is attributed to persistent virus expression in reservoirs and to cell activation. Of note, in CD4(+) T cells and monocyte-macrophages of virologically-suppressed individuals, there is continued expression of multi-spliced transcripts encoding HIV regulatory proteins. Among them, Tat is essential for virus gene expression and replication, either in primary infection or for virus reactivation during HAART, when Tat is expressed, released extracellularly and exerts, on both the virus and the immune system, effects that contribute to disease maintenance. Here we report results of an ad hoc exploratory interim analysis (up to 48 weeks) on 87 virologically-suppressed HAART-treated individuals enrolled in a phase II randomized open-label multicentric clinical trial of therapeutic immunization with Tat (ISS T-002). Eighty-eight virologically-suppressed HAART-treated individuals, enrolled in a parallel prospective observational study at the same sites (ISS OBS T-002), served for intergroup comparison. Immunization with Tat was safe, induced durable immune responses, and modified the pattern of CD4(+) and CD8(+) cellular activation (CD38 and HLA-DR) together with reduction of biochemical activation markers and persistent increases of regulatory T cells. This was accompanied by a progressive increment of CD4(+) T cells and B cells with reduction of CD8(+) T cells and NK cells, which were independent from the type of antiretroviral regimen. Increase in central and effector memory and reduction in terminally-differentiated effector memory CD4(+) and CD8(+) T cells were accompanied by increases of CD4(+) and CD8(+) T cell responses against Env and recall antigens. Of note, more immune-compromised individuals experienced greater therapeutic effects. In contrast, these changes were opposite, absent or partial in the OBS population. These findings support the use of Tat immunization to intensify HAART efficacy and to restore immune homeostasis. TRIAL REGISTRATION: ClinicalTrials.gov NCT00751595

    Patterns of clinical presentation of adult coeliac disease in a rural setting

    Get PDF
    BACKGROUND: In recent years there has been increasing recognition that the pattern of presentation of coeliac disease may be changing. The classic sprue syndrome with diarrhoea and weight loss may be less common than the more subtle presentations of coeliac disease such as an isolated iron deficiency anaemia. As a result, the diagnosis of this treatable condition is often delayed or missed. Recent serologic screening tests allow non-invasive screening to identify most patients with the disease and can be applied in patients with even subtle symptoms indicative of coeliac disease. Both benign and malignant complications of coeliac disease can be avoided by early diagnosis and a strict compliance with a gluten free diet. AIM: The aim of this study is to evaluate the trends in clinical presentation of patients diagnosed with adult coeliac disease. In addition, we studied the biochemical and serological features and the prevalence of associated conditions in patients with adult coeliac disease. METHODS: This is an observational, retrospective, cross-sectional review of the medical notes of 32 adult patients attending the specialist coeliac clinic in a district general hospital. RESULTS: Anaemia was the most common mode of presentation accounting for 66% of patients. Less than half of the patients had any of the classical symptoms of coeliac disease and 25% had none of the classical symptoms at presentation. Anti-gliadin antibodies, anti-endomysial antibody and anti-tissue transglutaminase showed 75%, 68% and 90% sensitivity respectively. In combination, serology results were 100% sensitive as screening tests for adult coeliac disease. Fifty nine percent patients had either osteoporosis or osteopenia. There were no malignant complications observed during the follow up of our patients. CONCLUSION: Most adults with coeliac disease have a sub clinical form of the disease and iron deficiency anaemia may be its sole presenting symptom. Only a minority of adult coeliac disease patients present with classical mal-absorption symptoms of diarrhoea and weight loss. Patients with atypical form of disease often present initially to hospital specialists other than a gastro-enterologist. An awareness of the broad spectrum of presentations of adult coeliac disease, among doctors both in primary care and by the various hospital specialists in secondary care, is necessary to avoid delays in diagnosis. It is important to include serological screening tests for coeliac disease systematically in the evaluation of adult patients with unexplained iron deficiency anaemia or unexplained gastro-intestinal symptoms and in those who are considered to be at increased risk for coeliac disease

    Evolution of scaling emergence in large-scale spatial epidemic spreading

    Get PDF
    Background: Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which is still hardly been clarified. Methodology/Principal Findings: In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States(U.S.) domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. Conclusions/Significance: The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.Comment: 24pages, 7figures, accepted by PLoS ON

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

    Full text link
    [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
    corecore