Book contents
- Cambridge Handbook of Psychology, Health and Medicine
- Cambridge Handbook of Psychology, Health and Medicine
- Copyright page
- Contents
- Contributors
- Preface
- Part I Psychology Health and Illness
- Section 1 Psychological Aspects of Health and Illness
- Section 2 Psychological Assessment
- Section 3 Psychological Interventions
- Section 4 Health Care Practice
- Part II Medical Topics
- Index
- References
Section 2 - Psychological Assessment
from Part I - Psychology Health and Illness
Published online by Cambridge University Press: 05 June 2019
Book contents
- Cambridge Handbook of Psychology, Health and Medicine
- Cambridge Handbook of Psychology, Health and Medicine
- Copyright page
- Contents
- Contributors
- Preface
- Part I Psychology Health and Illness
- Section 1 Psychological Aspects of Health and Illness
- Section 2 Psychological Assessment
- Section 3 Psychological Interventions
- Section 4 Health Care Practice
- Part II Medical Topics
- Index
- References
Summary
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- Type
- Chapter
- Information
- Cambridge Handbook of Psychology, Health and Medicine , pp. 173 - 236Publisher: Cambridge University PressPrint publication year: 2019
References
References
Chamberlain, S. R., Menzies, L., Hampshire, A., et al. (2008). Orbitofrontal dysfunction in patients with obsessive-compulsive disorder and their unaffected relatives. Science, 321(5887), 421–422. DOI: 10.1126/science.1154433.Google Scholar
Coleman, M. R., Davis, M. H., Rodd, J. M., et al. (2009). Towards the routine use of brain imaging to aid the clinical diagnosis of disorders of consciousness. Brain, 132(Pt 9), 2541–2552. DOI: 10.1093/brain/awp183.Google Scholar
Cruse, D., Chennu, S., Fernández-Espejo, D., et al. (2012). Detecting awareness in the vegetative state: electroencephalographic evidence for attempted movements to command, PLos One 7(11), e49933. DOI: 10.1371/journal.pone.0049933.CrossRefGoogle ScholarPubMed
Di, H., Boly, M., Weng, X., Ledoux, D. & Laureys, S. (2008). Neuroimaging activation studies in the vegetative state: predictors of recovery? Clinical Medicine Journal, 8(5), 502–507.CrossRefGoogle ScholarPubMed
Garrison, J. R., Fernyhough, C., McCarthy-Jones, S., et al. (2015). Paracingulate sulcus morphology is associated with hallucinations in the human brain. Nature Communications, 6, 8956. DOI: 10.1038/ncomms9956.CrossRefGoogle ScholarPubMed
Glasser, M. F., Smith, S. M., Marcus, D. S., et al. (2016). The Human Connectome Project’s neuroimaging approach. Nature Neuroscience, 19(9), 1175–1187. DOI: 10.1038/nn.4361.CrossRefGoogle ScholarPubMed
Haxby, J. V., Gobbini, M. I., Furey, M. L., et al. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293(5539), 2425–2430.Google Scholar
Haynes, J. D., Sakai, K., Rees, G., et al. (2007). Reading hidden intentions in the human brain. Current Biology, 17(4), 323–328.Google Scholar
Iacoboni, M., Freedman, J., Kaplan, J., et al. (2007). This is your brain on politics. New York Times. www.nytimes.com/2007/11/11/opinion/11freedman.html.Google Scholar
Kotwas, I., McGonigal, A., Trebuchon, A., et al. (2016). Self-control of epileptic seizures by nonpharmacological strategies. Epilepsy & Behavior, 55, 157–164. DOI: 10.1016/j.yebeh.2015.12.023.CrossRefGoogle ScholarPubMed
Lindstrom, M. (2011). You love your iPhone. Literally. New York Times. www.nytimes.com/2011/10/01/opinion/you-love-your-iphone-literally.html.Google Scholar
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal, Nature, 412(6843), 150–157.CrossRefGoogle ScholarPubMed
Minati, L. & Sigala, N. (2013). Effective connectivity reveals strategy differences in an expert calculator. PLoS One, 8(9), e73746. DOI: 10.1371/journal.pone.0073746.CrossRefGoogle Scholar
Moseley, R. L., Ypma, R. J., Holt, R. J., et al. (2015). Whole-brain functional hypoconnectivity as an endophenotype of autism in adolescents. NeuroImage: Clinical, 9, 140–152. DOI: 10.1016/j.nicl.2015.07.015.Google Scholar
Nature. (2016). Web focus on brain–machine interfaces. www.nature.com/nature/focus/brain/Google Scholar
O’Craven, K. M. & Kanwisher, N. (2000). Mental imagery of faces and places activates corresponding stiimulus-specific brain regions. Journal of Cognitive Neuroscience, 12(6), 1013–1023.Google Scholar
Owen, A. M., Coleman, M. R., Boly, M., et al. (2006). Detecting awareness in the vegetative state. Science, 313(5792), 1402. DOI: 10.1126/science.1130197.Google Scholar
Poldrack, R. A., Kittur, A., Kalar, D., et al. (2011). The Cognitive Atlas: toward a knowledge foundation for cognitive neuroscience. Frontiers in Neuroinformatics. DOI: http://dx.doi.org/10.3389/fninf.2011.00017.CrossRefGoogle Scholar
Saarimäki, H., Gotsopoulos, A., Jääskeläinen, I. P., et al. (2016). Discrete neural signatures of basic emotions. Cerebral Cortex, 26(6), 2563–2573.Google Scholar
Samuel, M., Williams, S. C., Leigh, P. N., et al. (1998). Exploring the temporal nature of hemodynamic responses of cortical motor areas using functional MRI. Neurology, 51(6), 1567–1575.Google Scholar
Schnakers, C., Perrin, F., Schabus, M., et al. (2009). Detecting consciousness in a total locked-in syndrome: an active event-related paradigm. Neurocase, 15(4), 271–277, DOI: 10.1080/13554790902724904.CrossRefGoogle Scholar
Schreiber, D., Fonzo, G., Simmons, A. N., et al. (2013). Red brain, blue brain: evaluative processes differ in Democrats and Republicans. PLoS One, 8(2), e52970. DOI: 10.1371/journal.pone.0052970.Google Scholar
Takahashi, H., Kato, M., Matsuura, M., et al. (2009). When your gain is my pain and your pain is my gain: neural correlates of envy and schadenfreude. Science, 323(5916): 937–939, DOI: 10.1126/science.1165604.Google Scholar
Thibault, R. T., Lifshitz, M. & Raz, A. (2016). The self-regulating brain and neurofeedback: experimental science and clinical promise, Cortex, 74, 247–261. DOI: 10.1016/j.cortex.2015.10.024.CrossRefGoogle ScholarPubMed
References
Andrews, G. & Peters, L. (1998). The psychometric properties of the Composite International Diagnostic Interview. Social Psychiatry and Psychiatric Epidemiology, 33(2), 80–88. DOI: 10.1007/s001270050026.CrossRefGoogle ScholarPubMed
Baker, F. M. & Bell, C. C. (1999). Issues in the psychiatric treatment of African Americans. Psychiatric Services, 50, 362–368. DOI: 10.1176/ps.50.3.362.Google Scholar
Christensen, K. S., Toft, T., Frostholm, L., et al. (2003). The FIP study: a randomized, controlled, trial of screening and recognition of psychiatric disorders. British Journal of General Practice, 53, 758–763.Google Scholar
First, M. B., Williams, J. B. W., Karg, R. S. & Spitzer, R. L. (2015a). Structured Clinical Interview for DSM-5-Research Version (SCID-5-RV). Arlington, VA: American Psychiatric Association.Google Scholar
First, M. B., Williams, J. B. W., Karg, R. S. & Spitzer, R. L. (2015b). Structured Clinical Interview for DSM-5 Disorders-Clinician Version (SCID-5-CV). Arlington, VA: American Psychiatric Association.Google Scholar
First, M. B., Williams, J. B. W., Benjamin, L. S. & Spitzer, R. L. (2015c) Structured Clinical Interview for DSM-5 Personality Disorders (SCID-5-PD). Arlington, VA: American Psychiatric Association.Google Scholar
Hare, R. D. (2003). Manual for the Revised Psychopathy Checklist (2nd edn). Toronto: Multi-Health Systems.Google Scholar
Jane, J. S., Pagan, J. L., Turkheimer, E., Fiedler, E. R. & Oltmanns, T. F. (2006). The interrater reliability of the Structured Interview for DSM-IV Personality. Comprehensive Psychiatry, 47(5), 368–375. DOI: 10.1016/j.comppsych.2006.01.009.Google Scholar
Kroenke, K., Spitzer, R. L., Williams, J. W., Monahan, P. O. & Löwe, B. (2007). Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Annals of Internal Medicine, 146(5), 317–377.Google Scholar
Lecrubier, Y., Sheehan, D., Weiller, E., et al. (1997). The Mini International Neuropsychiatric Interview (MINI): a short diagnostic structured interview – reliability and validity according to the CIDI. European Psychiatry, 12(5), 224–231. DOI: 10.1016/S0924-9338(97)83296-8.CrossRefGoogle Scholar
Loranger, A. W. (1999). International Personality Disorder Examination (IPDE) Manual. Lutz, FL: Psychological Assessment Resources.Google Scholar
Lowe, B., Spitzer, R. L., Gräfe, K., et al. (2004). Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses. Journal of Affective Disorders, 78, 131–140. DOI: 10.1016/S0165-0327(02)00237-9.CrossRefGoogle ScholarPubMed
Miller, P. R. (2001). Inpatient diagnostic assessments: 2. Interrater reliability of outcomes of structured vs. unstructured interviews. Psychiatry Research, 105(3), 265–271. DOI: 10.1016/S0165-1781(01)00318-3.Google Scholar
Mitchell, A. J., Vaze, A. & Rao, S. (2009). Clinical diagnosis of depression in primary care: a meta-analysis. Lancet, 374(9690), 609–619. DOI: 10.1016/S0140-6736(09)60879-5.Google Scholar
Noorthoorn, E. O., Havenaar, J. M., de Haan, H. A., van Rood, Y. R. & van Stiphout, W. J. (2010). Mental health service use and outcomes after the Enschede fireworks disaster: a naturalistic follow-up study. Psychiatric Services, 61(11), 1138–1143. DOI: 10.1176/appi.ps.61.11.1138.Google Scholar
North, C. S., Pollio, D. E., Thompson, S. J., et al. (1997). A comparison of clinical and structured interview diagnoses in a homeless mental health clinic. Community Mental Health Journal, 33, 531–543. DOI: 10.1023/A:1025052720325.Google Scholar
Pettersson, A., Boström, K. B., Gustavsson, P. & Ekselius, L. (2015). Which instruments to support diagnosis of depression have sufficient accuracy? A systematic review. Nordic Journal of Psychiatry, 69(7), 497–508. DOI: 10.3109/08039488.2015.1008568.Google Scholar
Pfohl, B., Blum, N. & Zimmerman, M. (1997). The Structured Interview for DSM-IV Personality: SIDP-IV. Washington, DC: American Psychiatric Press.Google Scholar
Rettew, D. C., Lynch, A. D., Achenbach, T. M., Dumenci, L. & Ivanova, M. Y. (2009). Meta-analyses of agreement between diagnoses made from clinical evaluations and standardized diagnostic interviews. International Journal of Methods in Psychiatric Research, 18(3), 169–184. DOI: 10.1002/mpr.289.Google Scholar
Robins, L. N., Helzer, J. E., Cottler, L. B. & Goldring, E. (1989). NIMH Diagnostic Interview Schedule, Version III – Revised. St. Louis, MO: Washington University School of Medicine.Google Scholar
Rogers, R. (2001). Handbook of Diagnostic and Structured Interviewing. New York: Guilford Publications.Google Scholar
Rogers, R. (2003). Standardizing DSM-IV diagnoses: the clinical applications of structured interviews. Journal of Personality Assessment, 81, 220–225.Google Scholar
Rogers, R., Jackson, R. L. & Cashel, M. L. (2003). SADS: comprehensive assessment of mood and psychotic disorders. In Hersen, M., Hilsenroth, M. J. & Segal, D. J. (eds), The Handbook of Psychological Assessment, Volume 2: Personality Assessment (pp. 144–152). New York: Wiley.Google Scholar
Ruggero, C. J., Zimmerman, M., Chelminski, I. & Young, D. (2010). Borderline personality disorder and the misdiagnosis of bipolar disorder. Journal of Psychiatric Research, 44(6), 405–408. DOI: 10.1016/j.jpsychires.2009.09.011.Google Scholar
Shear, M. K., Greeno, C., Kang, J., et al. (2000). Diagnosis of nonpsychotic patients in community clinics. American Journal of Psychiatry, 157, 581–587. DOI: 10.1176/appi.ajp.157.4.581.CrossRefGoogle ScholarPubMed
Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., et al. (1997). The validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. European Psychiatry, 12, 232–241. DOI: 10.1016/S0924-9338(97)83297-X.CrossRefGoogle Scholar
Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., et al. (1998). The Mini International Neuropsychiatric Interview (MINI): the development and validation of structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59 (Suppl. 20), 22–33.Google Scholar
Spitzer, R. L. & Endicott, J. (1978a). Schedule of Affective Disorders and Schizophrenia (3rd edn). New York: Biometrics Research.Google Scholar
Spitzer, R. L. & Endicott, J. (1978b). Schedule of Affective Disorders and Schizophrenia – Change Version. New York: Biometrics Research.Google Scholar
Swann, A. C., Lijffijt, M., Lane, S. D., Steinberg, J. L. & Moeller, F. G. (2013). Antisocial personality disorder and borderline symptoms are differentially related to impulsivity and course of illness in bipolar disorder. Journal of Affective Disorders, 148(2–3), 384–390. DOI: 10.1016/j.jad.2012.06.027.Google Scholar
Tausig, M., Subedi, J., Broughton, C., et al. (2011). The continued salience of methodological issues for measuring psychiatric disorders in international surveys. International Journal of Mental Health and Addiction, 9(3), 229–239. DOI: 10.1007/s11469-010-9276-3.Google Scholar
Tiemens, B. G., VonKorff, M. & Lin, E. H. B. (1999). Diagnosis of depression by primary care physicians versus a structured diagnostic interview. General Hospital Psychiatry, 21, 87–96. DOI: 10.1016/S0163-8343(98)00077-2.Google Scholar
Üstün, T. B. & von Korff, M. (1995). Primary mental health services: access and provision of care. In Üstün, T. B. & Sartorius, N. (eds), Mental Illness in General Health Care: An International Study (pp. 347–360). Chichester: John Wiley & Sons.Google Scholar
Ward, C. H., Beck, A. T., Mendelson, M., Mock, J. E. & Erbaugh, J. K. (1962). The psychiatric nomenclature: reasons for diagnostic disagreement. Archives of General Psychiatry, 7, 198–205. DOI: 10.1001/archpsyc.1962.01720030044006.Google Scholar
Williams, J. B., Gibbon, M., First, M. B., et al. (1992). The Structured Clinical Interview for DSM-III–R (SCID): II. Multisite test–retest reliability. Archives of General Psychiatry, 49(8), 630–636.Google Scholar
Wing, J. K., Sartorius, N. & Ustun, T. B. (1998). Diagnosis and Clinical Measurement in Psychiatry: A Reference Manual for SCAN/PSE-10. Cambridge: Cambridge University Press.Google Scholar
World Health Organization (1997). The Composite International Diagnostic Interview (Version 2, 12 Month). Geneva: World Health Organization.Google Scholar
Zimmerman, M. & Mattia, J. I. (1999). Psychiatric diagnosis in clinical practice: is comorbidity being missed? Comprehensive Psychiatry, 40, 182–191. DOI: 10.1016/S0010-440X(99)90001-9.Google Scholar
Zimmerman, M., Young, D., Chelminski, I., Dalrymple, K. & Galione, J. N. (2012). Overcoming the problem of diagnostic heterogeneity in applying measurement-based care in clinical practice: the concept of psychiatric vital signs. Comprehensive Psychiatry, 53(2), 117–124. DOI: 10.1016/j.comppsych.2011.03.004.Google Scholar
References
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th edn.). Arlington, VA: American Psychiatric Publishing.Google Scholar
Chafetz, M. & Underhill, J. (2013). Estimated costs of malingered disability. Archives of Clinical Neuropsychology, 28, 633–639.Google Scholar
Department of Veteran Affairs. (2013). Compensation. Washington, DC: Department of Veterans Affairs.Google Scholar
Department of Veterans Affairs Office of Inspector General. (2005). Review of State Variances in VA Disability Compensation Payments: Report No. 05-00765-137. Washington, DC: VA Office of Inspector General.Google Scholar
Elliott, T. R., Patnaik, A., Naiser, E., et al. (2014). Medicaid personal care services for children with intellectual disabilities: what assistance is provided? When is assistance provided? Intellectual and Developmental Disabilities, 52, 24–31.Google Scholar
Federici, S., Bracalenti, M., Meloni, F. & Luciano, J. V. (2016). World Health Organization disability assessment schedule 2.0: an international systematic review. Disability and Rehabilitation. DOI: 10.1080/09638288.2016.1223177.Google Scholar
Fuhrer, M. J. (ed.). (1987). Rehabilitation Outcomes: Analysis and Measurement. Baltimore, MD: Brookes.Google Scholar
Gholizadeh, S., Malcarne, V. L. & Schatman, M. E. (2015). Ethical quandaries for psychologists in workers’ compensation settings: the GAF gaffe. Psychological Injury and Law, 8(1), 64–81. DOI: 10.1007/s12207-015-9218-2.Google Scholar
Gold, L. H. (2014). DSM-5 and the assessment of functioning: the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Journal of the American Academy of Psychiatry and the Law, 42(2), 173–181.Google ScholarPubMed
Heinemann, A. W. & Mallinson, T. (2010). Functional status and quality-of-life measures. In Frank, R. G., Rosenthal, M. & Caplan, B. (eds), Handbook of Rehabilitation Psychology (2nd edn.; pp. 147–164). Washington, DC: American Psychological Association.Google Scholar
IOM (Institute of Medicine). (2015). Psychological Testing in the Service of Disability Determination. Washington, DC: National Academies Press.Google Scholar
Keith, R. A., Granger, C. V., Hamilton, B. B. & Sherwin, F. S. (1987). The functional independent measure: a new tool for rehabilitation. Advances in Clinical Rehabilitation, 1, 6–18.Google Scholar
Marx, B. P., Wolf, E. J., Cornette, M., et al. (2015). Using the WHODAS 2.0 to assess functioning among veterans seeking compensation for posttraumatic stress disorder. Psychiatric Services, 66(12), 1312–1317. DOI: 10.1176/appi.ps.201400400.Google Scholar
Marx, B. P., Bovin, M. J., Szafranski, D. D., et al. (2016). Validity of posttraumatic stress disorder service connection status in Veterans Affairs electronic records of Iraq and Afghanistan veterans. Journal of Clinical Psychiatry, 77(4), 517–522. DOI: 10.4088/JCP.14m09666.Google Scholar
Musumeci, M. (2011). Modernizing Medicaid eligibility criteria for children with significant disabilities: moving from a disabling to an enabling paradigm. American Journal of Law & Medicine, 37, 81–127.Google Scholar
Piechowski, L. D. (2013). Disability and workers compensation. In Otto, R. K. & Weiner, I. B. (eds), Handbook of Psychology (2nd edn.; Vol. 11; pp. 201–224). Hoboken, NJ: John Wiley & Sons, Inc.Google Scholar
Russo, A. C. (2014). Assessing veteran symptom validity. Psychological Injury and Law, 7, 178–190.CrossRefGoogle Scholar
Social Security Administration (SSA). (2013a). Annual Statistical Report on the Social Security Disability Insurance Program, 2012. www.socialsecurity.gov/policy/docs/statcomps/di_asr/2012/index.htmlGoogle Scholar
Social Security Administration (SSA). (2013b). SSI Annual Statistical Report, 2012. www.socialsecurity.gov/policy/docs/statcomps/ssi_asr/2012/index.htmlGoogle Scholar
Tabernik, H. & Vitacco, M. J. (2015). Finding the truth in the lies: a practical guide to the assessment of malingering. In Bhugra, D. & Malhi, G. S. (eds), Troublesome Disguises: Managing Challenging Disorders in Psychiatry (2nd edn.; pp. 85–99). Chichester: Wiley-Blackwell.Google Scholar
Veteran Benefits Administration. (2013). Annual Benefits Report. Washington, DC: Veterans Benefits Administration.Google Scholar
Wise, E. A. (2016). Psychological injuries, workers’ compensation insurance, and mental health policy issues. Psychological Injury and Law, 9(4), 283–297.Google Scholar
World Health Organization. (2001). International Classification of Functioning, Disability, and Health. Geneva: World Health Organization.Google Scholar
Worthen, M. D. & Moering, R. G. (2011). A practical guide to conducting VA compensation and pension exams for PTSD and other mental disorders. Psychological Injury and Law, 4, 187–216.Google Scholar
Young, G. (2015). Towards balanced VA and SSA policies in psychological injury disability assessment. Psychological Injury and Law, 8(3), 200–218. DOI: 10.1007/s12207-015-9230-6.Google Scholar
References
Bean, D., Cundy, T. & Petrie, K. J. (2007). Ethnic differences in illness perceptions, self-efficacy and diabetes self-care. Psychology & Health, 22, 787–811.Google Scholar
Benyamini, Y., Gozlan, M. & Kokia, E. (2009). Women’s and men’s perceptions of infertility and their associations with psychological adjustment: a dyadic approach. British Journal of Health Psychology, 14, 1–16.CrossRefGoogle ScholarPubMed
Broadbent, E. & Richardson, A. E. (2015). Interventions to change illness perceptions. In Henningsen, P. & Rief, W. (eds), Psychosomatik und Verhaltensmedizin. Stuttgart: Schattauer Publishing.Google Scholar
Broadbent, E., Petrie, K. J., Ellis, C. J., Ying, J. & Gamble, G. (2004). A picture of health: myocardial infarction patients’ drawings of their hearts and subsequent disability: a longitudinal study. Journal of Psychosomatic Research, 57, 583–587. DOI: 10.1016/j.jpsychores.2004.03.014.Google Scholar
Broadbent, E., Petrie, K. J., Main, J. & Weinman, J. (2006a). The Brief Illness Perception Questionnaire. Journal of Psychosomatic Research, 60, 631–637. DOI: 10.1016/j.jpsychores.2005.10.020.Google Scholar
Broadbent, E., Ellis, C. J., Gamble, G. & Petrie, K. J. (2006b). Changes in patient drawings of the heart identify slow recovery after myocardial infarction. Psychosomatic Medicine, 68, 910–913. DOI: 10.1097/01.psy.0000242121.02571.10.Google Scholar
Broadbent, E., Ellis, C. J., Thomas, J., Gamble, G. & Petrie, K. J. (2009a). Can an illness perception intervention reduce illness anxiety in spouses of myocardial infarction patients? A randomized controlled trial. Journal of Psychosomatic Research, 67, 11–15. DOI: 10.1016/j.jpsychores.2008.11.006.Google Scholar
Broadbent, E., Niederhoffer, K., Hague, T., Corter, A. & Reynolds, L. (2009b). Headache sufferers’ drawings reflect distress, disability and illness perceptions. Journal of Psychosomatic Research, 66, 465–470.Google Scholar
Broadbent, E., Donkin, L. & Stroh, J. C. (2011). Illness and treatment perceptions are associated with adherence to medications, diet, and exercise in diabetic patients. Diabetes Care, 34, 338–340. DOI: 34/2/338 [pii] 10.2337/dc10-1779.Google Scholar
Broadbent, E., Wilkes, C., Koschwanez, H., et al. (2015). A systematic review and meta-analysis of the Brief Illness Perception Questionnaire. Psychology & Health, 30, 1361–1385.Google Scholar
Brooks, S., Rowley, S., Broadbent, E. & Petrie, K. J. (2012). Illness perception ratings of high-risk newborns by mothers and clinicians: relationship to illness severity and maternal stress. Health Psychology, 31, 632–639. DOI: 10.1037/a0027591.Google Scholar
Carpenter, C. J. (2010). A meta-analysis of the effectiveness of health belief model variables in predicting behavior. Health Communication, 25, 661–669. DOI: 10.1080/10410236.2010.521906Google Scholar
Chilcot, J., Wellsted, D. & Farrington, K. (2011). Illness perceptions predict survival in haemodialysis patients. American Journal of Nephrology, 33, 358–363.Google Scholar
Chong, J., Mackey, A. H., Broadbent, E. & Stott, N. S. (2012). Children’s perceptions of their cerebral palsy and their impact on life satisfaction. Disability and Rehabilitation, 34, 2053–2060. DOI: 10.3109/09638288.2012.669021.Google Scholar
Clatworthy, J., Hankins, M., Buick, D., Weinman, J. & Horne, R.. (2007). Cluster analysis in illness perception research: a Monte Carlo study to identify the most appropriate method. Psychology and Health, 22, 123–142.Google Scholar
Corace, K. M., Srigley, J. A., Hargadon, D. P., et al. (2016). Using behavior change frameworks to improve healthcare worker influenza vaccination rates: a systematic review. Vaccine, 34, 3235–3242. DOI: 10.1016/j.vaccine.2016.04.071.Google Scholar
Fiske, S. T. & Taylor, S. E. (2013). Social Cognition: From Brains to Culture. New York: Sage.Google Scholar
Grünich, K., Garcia-Hoyos, V., Stinear, C., et al. (2016). Kinematic measures of brain drawings are associated with illness perceptions in people with stroke. International Psychogeriatrics, 28: 1637–1642.Google Scholar
Hagger, M. S. & Orbell, S. (2003). A meta-analytic review of the common-sense model of illness representations. Psychology & Health, 18, 141–184.Google Scholar
Hampson, S. E., Glasgow, R. E. & Toobert, D. J. (1990). Personal models of diabetes and their relations to self-care activities. Health Psychology, 9, 632.Google Scholar
HayslipJr, B., Weigand, D., Weinberg, R., Richardson, P. & Jackson, A. (1996). The development of new scales for assessing health belief model constructs in adulthood. Journal of Aging and Physical Activity, 4, 307–323.Google Scholar
Horne, R. & Weinman, J. (2002). Self-regulation and self-management in asthma: exploring the role of illness perceptions and treatment beliefs in explaining non-adherence to preventer medication. Psychology and Health, 17, 17–32.Google Scholar
Jones, A. S. K., Ellis, C. J., Nash, M., Stanfield, B. & Broadbent, E. (2016a). Using animation to improve recovery from acute coronary syndrome: a randomized trial. Annals of Behavioral Medicine, 50, 108–118.Google Scholar
Jones, K. M., Kydd, R., Broadbent, E., et al. (2016b). Brain drawings following traumatic brain injury (TBI) and links to illness perceptions and health outcomes: findings from a population-based study. Psychology & Health, 31, 1182–1202.Google Scholar
Jones, K. M., Theadom, A., Barker-Collo, S., et al. (in press). Associations between brain drawings following mild traumatic brain injury and negative illness perceptions and post-concussion symptoms at four-years. Journal of Health Psychology. DOI: 10.1177/1359105317695430.Google Scholar
Kaptein, A. A., Bijsterbosch, J., Scharloo, M., et al. (2010). Using the common sense model of illness perceptions to examine osteoarthritis change: a 6-year longitudinal study. Health Psychology, 29, 56.Google Scholar
Kung, M., Koschwanez, H. E., Painter, L., Honeyman, V. & Broadbent, E. (2012). Immunosuppressant nonadherence in heart, liver, and lung transplant patients: associations with medication beliefs and illness perceptions. Transplantation, 93, 958–963.Google Scholar
Lau, R. R. & Hartman, K. A. (1983). Common sense representations of common illnesses. Health Psychology, 2, 167–185.Google Scholar
Leventhal, H., Meyer, D. & Nerenz, D. R. (1980). The common sense representations of illness danger. In Rachman, S. (ed.), Medical Psychology (Vol. 2; pp. 7–30). New York: Pergamon.Google Scholar
Leventhal, H., Nerenz, D. R. & Steele, D. S. (1984). Illness representations and coping with health threats. In Baum, A. & Singer, J. E. (eds), Handbook of Psychology and Health (Vol. 4; pp. 221–252). New York: Erlbaum.Google Scholar
Lobban, F., Barrowclough, C. & Jones, S. (2004). The impact of beliefs about mental health problems and coping on outcome in schizophrenia. Psychological Medicine, 34, 1165–1176.CrossRefGoogle ScholarPubMed
Lobban, F., Barrowclough, C. & Jones, S. (2005). Assessing cognitive representations of mental health problems. I. The illness perception questionnaire for schizophrenia. British Journal of Clinical Psychology, 44, 147–162.Google Scholar
Logan, R. L. (1986). Patient drawings as aids to the identification and management of causes of distress and atypical symptoms in cardiac patients. New Zealand Medical Journal, 99, 368–371.Google Scholar
Moss-Morris, R., Weinman, J., Petrie, K. J., et al. (2002). The Revised Illness Perception Questionnaire (IPQ-R). Psychology & Health, 17, 1–16.Google Scholar
Parfeni, M., Nistor, I. & Covic, A. (2013). A systematic review regarding the association of illness perception and survival among end-stage renal disease patients. Nephrology Dialysis Transplantation, 28, 2407–2414.Google Scholar
Petrie, K. J., Broadbent, E. & Kydd, R. (2008). Illness perceptions in mental health: issues and potential applications. Journal of Mental Health, 17, 559–564. DOI: 10.1080/09638230802523047.Google Scholar
Richardson, A. E., Morton, R. P. & Broadbent, E. A. (2016). Changes over time in head and neck cancer patients’ and caregivers’ illness perceptions and relationships with quality of life. Psychology & Health, 31, 1203–1219. DOI: 10.1080/08870446.2016.1203686.Google Scholar
Roesch, S. C. & Weiner, B. (2001). A meta-analytic review of coping with illness: do causal attributions matter? Journal of Psychosomatic Research, 50, 205–219.Google Scholar
Rosenstock, I. M. (1974). The health belief model and preventive health behavior. Health Education Monographs, 2, 354–386.Google Scholar
Rosenstock, I. M., Strecher, V. J. & Becker, M. H. (1988). Social learning theory and the health belief model. Health Education & Behavior, 15(2), 175–183.Google Scholar
Saunders, G. H., Frederick, M. T., Silverman, S. & Papesh, M. (2013). Application of the health belief model: development of the Hearing Beliefs Questionnaire (HBQ) and its associations with hearing health behaviors. International Journal of Audiology, 52, 558–567. DOI: 10.3109/14992027.2013.791030.Google Scholar
Scharloo, M. & Kaptein, A. (1997). Measurement of illness perceptions in patients with chronic somatic illness: a review. In Petrie, K. J. & Weinman, J. A. (eds), Perceptions of Health and Illness: Current Research and Applications (pp. 103–154). Amsterdam: Harwood Academic Publishers.Google Scholar
Schneider, C.A., Rasband, W. S. & Eliceiri, K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods, 9, 671.Google Scholar
Serlachius, A., Gamble, G., House, M., et al. (2016). Illness perceptions predict mortality in patients with gout: a prospective observational study. Arthritis Care & Research. DOI: 10.1002/acr.23147.Google Scholar
Strecher, V. J. & Rosenstock, I. M. (1997). The health belief model. In Baum, A., Newman, S., Weinman, J., West, R. & McManus, C. (eds), Cambridge Handbook of Psychology, Health and Medicine (pp. 113–117). Cambridge: Cambridge University Press.Google Scholar
van Leeuwen, B. M., Herruer, J. M., Putter, H., van der Mey, A. G. & Kaptein, A. A. (2015). The art of perception: patients drawing their vestibular schwannoma. Laryngoscope, 125, 2660–2667. DOI: 10.1002/lary.25386.Google Scholar
Weinman, J., Petrie, K. J., Moss-Morris, R. & Horne, R. (1996). The Illness Perception Questionnaire: a new method for assessing the cognitive representation of illness. Psychology & Health, 11, 114–129.Google Scholar
Weinman, J., Petrie, K. J., Sharpe, N. & Walker, S. (2000). Causal attributions in patients and spouses following first-time myocardial infarction and subsequent lifestyle changes. British Journal of Health Psychology, 5, 263–273.Google Scholar
References
Abbey, A. & Andrews, F. M. (1986). Modelling the psychological determinants of life quality. In: Andrews, F. M. (ed.), Research on the Quality of Life. Ann Arbor, MI: Survey Research Center, Institute for Social Research, University of Michigan.Google Scholar
Andrews, F M. (ed.). (1986). Research on the Quality of life. Ann Arbor, MI: University of Michigan, Institute for Social Research.Google Scholar
Andrews, F. M. & Withey, S. B. (1974). Developing measures of perceived life quality: results from several national surveys. Social Indicators Research, 1: 1–26.CrossRefGoogle Scholar
Beckie, T. M. & Hayduk, L. A. (1997). Measuring quality of life. Social Indicators Research, 42, 21–39.Google Scholar
Bowling, A. (2001). Measuring Disease: A Review of Disease-Specific Quality of Life Measurement Scales (2nd edn). Milton Keynes: Open University Press.Google Scholar
Bowling, A. (2005). Just one question: if one question works why ask several? Editorial. Journal of Epidemiology and Community Health, 59, 342–345.Google Scholar
Bowling, A. (2009). Psychometric properties of the Older People’s Quality of Life Questionnaire Validity. Current Gerontology and Geriatrics Research. www.hindawi.com/journals/cggr/2009/298950.abs.htmlCrossRefGoogle Scholar
Bowling, A. (2016). Measuring Health (4th edn). Maidenhead: McGraw-Hill Education, Open University Press.Google Scholar
Bowling, A. & Stenner, P. (2011). Which measure of quality of life performs best in older age? A comparison of the OPQOL, CASP-19 and WHOQOL-OLD. Journal of Epidemiology and Community Health, 65, 273–280.Google Scholar
Bowling, A. & Windsor, J. (2008). The effects of question order and response-choice on self-rated health status in the English Longitudinal Study of Ageing (ELSA). Journal of Epidemiology and Community Health, 62, 81–85.Google Scholar
Bowling, A., Hankins, M., Windle, G., et al. (2013). A short measure of quality of life in older age: the performance of the brief Older People’s Quality of Life questionnaire (OPQOL-brief). Archives of Geriatrics and Gerontology, 56(1), 181–187.Google Scholar
Brissette, I., Leventhal, H. & Leventhal, E. A. (2003). Observer ratings of health and sickness: can other people tell us anything about our health that we don’t already know? Health Psychology, 22, 471–478.Google Scholar
Browne, J. P., O’Boyle, C. A., McGee, H. M., et al. (1997). Development of a direct weighing procedure for quality of life domains. Quality of Life Research, 6, 301–309.Google Scholar
DeSalvo, K. B., Bloser, N., Reynolds, K., et al. (2006). Mortality prediction with a single general self-rated health question. Journal of General Internal Medicine, 21, 267–275.Google Scholar
Farquhar, M. (1995). Definitions of quality of life: a taxonomy. Journal of Advanced Nursing, 22, 502–508.CrossRefGoogle ScholarPubMed
Fayers, P. M. & Hand, D. J. (2002). Causal variables, indicator variables and measurement scales: an example from quality of life. Journal of the Royal Statistical Association, 165, Part 2, 1–21.Google Scholar
Fry, P. S. (2000). Whose quality of life is it anyway? Why not ask seniors to tell us about it? International Journal of Aging and Human Development, 50, 361–383.Google Scholar
Garratt, A., Schmidt, L., Mackintosh, A. & Fitzpatrick, R. (2002). Quality of life measurement: bibliographic study of patient assessed health outcome measures. British Medical Journal, 324, 1417.Google Scholar
Headey, B. W., Glowacki, T., Holmstrom, E. L. & Wearing, A. J. (1985). Modelling change in perceived quality of life. Social Indicators Research, 17, 276–298.Google Scholar
Higgs, P., Hyde, M., Wiggins, R. & Blane, D. (2003). Researching quality of life in early old age: the importance of the sociological dimension. Social Policy and Administration, 37, 239–252.Google Scholar
Hyde, M., Wiggins, R. D., Higgs, P. & Blane, D. (2003). A measure of quality of life in early old age: the theory, development and properties of a needs satisfaction model (CASP-19). Aging and Mental Health, 7: 186–194.Google Scholar
Hyde, M., Higgs, P.,Wiggins, R. D. & Blane, D. (2015). A decade of research using the CASP scale: key findings and future directions. Aging and Mental Health, 19(7), 571–575.Google Scholar
Kaplan, R. M. (1988). New health promotion indicators: the general health policy model. Health Promotion, 3, 35–48.Google Scholar
Larson, R. (1978). Thirty years of research on the subjective well-being of older Americans. Journal of Gerontology, 33, 109–125.Google Scholar
Lawton, M. P. (1991). ‘A Multidimensional View of Quality of Life in Frail Elders’. In Birren, J. E., Lubben, J., Rowe, J., Deutchman, D. (eds)., The Concept and Measurement of Quality of Life. New York: Academic Press.Google Scholar
Malley, J. N., Towers, A.-M., Netten, A. P., et al. (2012). An assessment of the construct validity of the ASCOT measure of social care-related QoL with older people. Health and QoL Outcomes, 10:21. DOI: 10.1186/1477-7525-10-21.CrossRefGoogle Scholar
Maslow, A. H. (1962). Toward a Psychology of Being (2nd edn). Princeton, NJ: Van Nostrand.Google Scholar
McDowell, I. (2006). Measuring Health: A Guide to Rating Scales and Questionnaires (3rd edn). New York: Oxford University Press.Google Scholar
McDowell, I. & Newell, C. (1996). Measuring Health: A Guide to Rating Scales and Questionnaires (2nd edn). New York: Oxford University Press.Google Scholar
Michalos, A. C. (1986). Job satisfaction, marital satisfaction and the quality of life: a review and preview. In Andrews, F. M. (ed.), Research on the Quality of life. Ann Arbor, MI: Survey Research Center, Institute for Social research, University of Michigan.Google Scholar
Netten, A., Beadle Brown, J., Caiels, J., et al. (2011). ASCOT adult social care outcomes toolkit. Main guidance v2.1. PSSRU Discussion Paper 2716/3.Google Scholar
Netten, A., Burge, P., Malley, J., et al. (2012). Outcomes of social care for adults: developing a preference-weighted measure. Health Technology Assessment, 16, 16.Google Scholar
O’Boyle, C. A. (1997). Measuring the quality of later life. Philosophal Transactions of the Royal Society of London, 352, 1871–1879.Google Scholar
Patrick, D. L. & Erickson, P. (1993). Health Status and Health Policy: Quality of Life in Health Care Evaluation and Resource Allocation. New York: Oxford University Press.Google Scholar
Power, M., Harper, A., Bullinger, M. & WHO Quality of Life Group (1999). The World Health Organization WHOQOL-100: tests of the universality of quality of life in 15 different cultural groups worldwide. Health Psychology, 18, 495–505.Google Scholar
Power, M., Quinn, K., Schmidt, S. & WHOQOL-OLD Group. (2005). Development of WHOQOL-OLD module. Quality of Life Research, 14, 2197–2214.Google Scholar
Rosenberg, R. (1995). Health-related quality of life between naturalism and hermeneutics. Social Science and Medicine, 10, 1411–1415.Google Scholar
Siegel, M., Bradley, E. H. & Kasl, S. V. (2003). Self-rated life expectancy as a predictor of mortality: evidence from the HRS and AHEAD surveys. Gerontology, 49, 265–271.Google Scholar
Skevington, S. M. (1999). Measuring quality of life in Britain: introducing the WHOQOL-100. Psychomatic Research, 47, 449–459.Google Scholar
Skevington, S. M., Carse, M. S. & de Williams, C. (2001). Validation of the WHOQOL-100: pain management improves quality of life for chronic pain patients. Clinical Journal of Pain, 17, 264–275.Google Scholar
Skevington, S. M., Lotfy, M. & O’Connell, K. A. (2004). The World Health Organization’s WHOQOLBREF quality of life assessment: psychometric properties and results of international field trials. A report from the WHOQOL Group. Quality of Life Research, 13, 299–310.Google Scholar
Spilker, B. (ed.) (1996). Pharmacoeconomics and Quality of Life in Clinical Trials (2nd edn). Philadelphia, PA: Lippincott-Raven.Google Scholar
Spiro, A. & Bossè, R. (2000). Relations between health-related quality of life and well-being: the gerontologist’s new clothes. International Journal of Aging and Human Development, 50: 297–318.Google Scholar
Sprangers, M. A. G. & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: a theoretical model. Social Science and Medicine, 48, 1507–1515.Google Scholar
Stewart, A. L., Ware, J. E., Brook, R. H., et al. (1978). Conceptualization and Measurement of Health for Adults in the Health Insurance Study: vol. II: Physical Health in Terms of Functioning. Santa Monica, CA: Rand Corporation.Google Scholar
Ware, J. E., Snow, K. K., Kosinski, M. & Gandek, B. (1993). SF-36 Health Survey: Manual and Interpretation Guide. Boston, MA: The Health Institute, New England Medical Center.Google Scholar
Ware, J. E., Snow, K. K., Kosinski, M. & Gandek, B. (1997). SF-36 Health Survey: Manual and Interpretation Guide (revised edition). Boston, MA: The Health Institute, New England Medical Center.Google Scholar
WHOQOL Group (1993). Measuring Quality of life: The Development of the World Health Organization Quality of Life Instrument (WHOQOL). Geneva: World Health Organization.Google Scholar
WHOQOL Group (1995). The World Health Organization quality of life assessment (WHOQOL): position paper from the World Health Organization. Social Science and Medicine, 10, 1403–1409.Google Scholar
WHOQOL Group (1998). Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment. Psychological Medicine, 28: 551–558.Google Scholar
World Health Organization (1947). Constitution of the World Health Organization. Geneva: World Health Organization.Google Scholar
World Health Organization (1984). Uses of Epidemiology in Aging: Report of a Scientific Group, 1983. Geneva: World Health Organization.Google Scholar
Zissi, A., Barry, M. M. & Cochrane, R. (1998). A mediational model of quality of life for individuals with severe mental health problems. Psychological Medicine, 28, 1221–1230.Google Scholar
References
Binet, A. & Simon, T. (1916). The Development of Intelligence in Children. Baltimore, MD: Williams & Wilkins. (Originally published in 1905).Google Scholar
Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor-Analytic Studies. New York: Cambridge University Press.Google Scholar
Cattell, R. B. (1971). Abilities: Their Structure, Growth and Action. Boston, MA: Houghton Mifflin.Google Scholar
Eyferth, K. (1961). Leistungen verschiedener Gruppen von Besatzungskindern im Hamburg-Wechsler Intelligenztest für Kinder (HAWIK). Archiv für die gesamte Psychologie, 113, 222–241.Google Scholar
Halpern, D. F., Beninger, A. S. & Straight, C. A. (2011). Sex differences in intelligence. In Sternberg, R. J. & Kaufman, S. B. (eds), Cambridge Handbook of Intellience (pp. 253–272). New York: Cambridge University Press.Google Scholar
Jensen, A. R. (1998). The g Factor: The Science of Mental Ability. Westport, CT: Praeger/Greenwoood.Google Scholar
Mackintosh, N. J. (2011). IQ and Human Intelligence (2nd edn). Oxford: Oxford University Press.Google Scholar
Mandelbaum, S. D. & Grigorenko, E. L. (2011). Intelligence: genes, environments, and their interactions. In Sternberg, R. J. & Kaufman, S. B. (Eds.), Cambridge Handbook of Intelligence (pp. 85–106). New York: Cambridge University Press.Google Scholar
Moore, E. G. J. (1986). Family socialization and the IQ test performance of traditionally and transracially adopted black children. Developmental Psychology, 22, 317–326.Google Scholar
Roid, G. (2003). Stanford–Binet Intelligence Scales, (5th edn). Itasca, IL: Riverside.Google Scholar
Steele, C. M. (1997). A threat in the air: how stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613–629.Google Scholar
Sternberg, R. J. (1990). Metaphors of Mind: Conceptions of the Nature of Intelligence. New York: Cambridge University Press.Google Scholar
Sternberg, R. J. (2002). Beyond g: the theory of successful intelligence. In Sternberg, R. J. & Grigorenko, E. L. (eds.), The General Factor of Intelligence: How General Is It? Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Sternberg, R. J. (2004). Culture and intelligence. American Psychologist, 59, 325–338.Google Scholar
Sternberg, R. J. (2010). College Admissions for the 21st Century. Cambridge, MA: Harvard University Press.Google Scholar
Sternberg, R. J. (2015). Multiple intelligences in the new age of thinking. In Goldstein, S., Princiotta, D. & Naglieri, J. A. (eds), Handbook of Intelligence (pp. 229–242). New York: Springer.Google Scholar
Sternberg, R. J. & Detterman, D. K. (eds) (1986). What is Intelligence? Norwood, NJ: Ablex Publishing Corporation.Google Scholar
Terman, L. M. (1916). The Measurement of Intelligence: An Explanation of and a Complete Guide for the Use of the Stanford Revision and Extension of the Binet–Simon Intelligence Scale. Boston, MA: Houghton Mifflin.Google Scholar
Thorndike, E. L. (1921) ‘Intelligence and its measurement’: a symposium. Journal of Educational Psychology, 12, 123–147, 195–216, 271–275.Google Scholar
Wechsler, D. (1974). The Measurement and Appraisal of Adult Intelligence. Baltimore, MD: Williams & Wilkins.Google Scholar
Willis, J. O., Dumont, R. & Kaufman, A. S. (2011). Factor-analytic models of intelligence. In Sternberg, R. J. & Kaufman, S. B. (eds), Cambridge Handbook of Intelligence (pp. 39–57.) New York: Cambridge University Press.Google Scholar
References
Barrett, L. F. (2004). Feelings or words? Understanding the content in self-report ratings of emotional experience. Journal of Personality and Social Psychology, 87, 266–281.Google Scholar
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J. & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561–571.Google Scholar
Bennett, M. P., Zeller, J. M., Rosenberg, L. & McCann, J. (2003). The effect of mirthful laughter on stress and natural killer cell activity. Alternative Therapies in Health and Medicine, 9(2), 38–45.Google Scholar
Benyamini, Y., Roziner, I., Goldbourt, U., Drory, Y. & Gerber, Y. (2013). Depression and anxiety following myocardial infarction and their inverse associations with future health behaviors and quality of life. Annals of Behavioral Medicine, 46, 310–321.Google Scholar
Cacioppo, J. T., Bernston, G. G., Larsen, J. T., Poehlmann, K. M. & Ito, T. A. (2000). The psychophysiology of emotion. In Lewis, R. & Haviland-Jones, J. M. (eds.), The Handbook of Emotion (2nd edn.; pp. 173–191). New York: Guilford.Google Scholar
Carver, C. S. & Scheier, M. F. (1998). On the Self-Regulation of Behavior. New York: Cambridge University Press.Google Scholar
Chaput, L. A., Adams, S. H., Simon, J. A., et al. (2002). Hostility predicts recurrent events among postmenopausal women with coronary heart disease. American Journal of Epidemiology, 156, 1092–1099.Google Scholar
Christie, I. C. & Friedman, E. H. (2004). Autonomic specificity of discrete emotion and dimensions of affective space: a multivariate approach. International Journal of Psychophysiology, 51, 143–153.Google Scholar
Clark, A., Seidler, A. & Miller, M. (2001). Inverse association between sense of humor and coronary heart disease. International Journal of Cardiology, 80(1), 87–88.Google Scholar
Cohen, S., Doyle, W. J., Turner, R., Alper, C. M. & Skoner, D. P. (2003). Sociability and susceptibility to the common cold. Psychological Science, 14(5), 389–395.Google Scholar
Danner, D. D., Snowdon, D. A. & Friesen, W. V. (2001). Positive emotions in early life and longevity: findings from the nun study. Journal of Personality and Social Psychology, 80(5), 804–813.Google Scholar
Davis, M. C., Matthews, K. A. & McGrath, C. (2000). Hostile attitudes predict elevated vascular resistance to interpersonal strata in both men and women. Psychosomatic Medicine, 62, 17–25.Google Scholar
Davydov, D. M., Zech, E. & Luminet, O. (2011). Affective context of sadness and physiological response patterns. Journal of Psychophysiology, 25, 67–80.Google Scholar
Derogatis, L. R. (1996). Derogatis Affects Balance Scale (DABS): Preliminary Scoring, Procedures & Administration Manual. Baltimore, MD: Clinical Psychometric Research.Google Scholar
Faber, S. D. & Burns, J. W. (1996). Anger management style, degree of expressed anger, and gender influence cardiovascular recovery from interpersonal harassment. Journal of Behavioral Medicine, 19, 31–53.Google Scholar
Feldman, L. A. (1993). Distinguishing depression from anxiety in self-report: evidence from confirmatory factor analysis on nonclinical and clinical samples. Journal of Consulting and Clinical Psychology, 61, 631–638.Google Scholar
Fernández, C., Pascual, J. C., Soler, J., et al. (2012). Physiological responses induced by emotion-eliciting films. Applied Psychophysiology and Biofeedback, 37, 73–79.Google Scholar
Fredrickson, B. L. (2000). Extracting meaning from past affective experiences: the importance of peaks, ends, and specific emotions. Cognition and Emotion, 14(4), 577–606.Google Scholar
Fredrickson, B. L., Mancuso, R. A., Branigan, C. & Tugade, M. M. (2000). The undoing effect of positive emotions. Motivation and Emotion, 24, 237–258.Google Scholar
Harley, J. M., Bouchet, F., Hussain, M. S., Azevedo, R. & Calvo, R. (2015). A multi- componential analysis of emotions during complex learning with an intelligent multi-agent system. Computers in Human Behavior, 48, 615–625.Google Scholar
Hathaway, S. R. & McKinley, J. C. (1989). Minnesota Multiphasic Personality Inventory-2 (MMPI-2): Manual for Administration and Scoring. Minneapolis, MN: University of Minnesota Press.Google Scholar
James, W. (1884/1969). What is an emotion? In William James: Collected essays and Reviews (pp. 244–80). New York: Russell and Russell.Google Scholar
Jenson, M. R. (1987). Psychobiological factors predicting the course of breast cancer. Journal of Personality, 55, 317–342.Google Scholar
Kawachi, I., Sparrow, D., Spiro, A., Vokonas, P. & Weiss, S. T. (1996). A prospective study of anger and coronary heart disease: the normative aging study. Circulation, 94(9), 2090–2095.Google Scholar
Key, B. L., Campbell, T. S., Bacon, S. L. & Gerin, W. (2008). The influence of trait and state rumination on cardiovascular recovery from a negative emotional stressor. Journal of Behavioral Medicine, 31, 237–248.Google Scholar
Kubzansky, L. D. & Arthur, C. M. (2004). Anxiety, heart disease, and mortality. In Anderson, N. (ed.), Emotional Longevity (pp. 55–59). New York: Viking.Google Scholar
Kubzansky, L. D. & Kawachi, I. (2000). Going to the heart of the matter: do negative emotions cause coronary heart disease? Manual of Psychosomatic Research, 48, 323–337.Google Scholar
Kubzansky, L. D. & Kawachi, I. (2002). Affective states and health. In Berkman, L. F. & Kawachi, I. (eds), Social Epidemiology (pp. 213–241). New York: Oxford University Press.Google Scholar
Lewinski, P. (2015). Don’t look blank, happy, or sad: patterns of facial expressions of speakers in banks’ YouTube videos predict video’s popularity over time. Journal of Neuroscience, Psychology, and Economics, 8, 241–249.Google Scholar
MacDougall, J. M., Dembroski, T. M., Dimsdale, J. E. & Hackett, T. P. (1985). Components of Type-A, hostility and anger-in: further relationships to angiographic findings. Health Psychology, 4, 137–152.Google Scholar
Markovitz, J. H., Matthews, K. A., Wing, R. R., Kuller, L. H. & Meilahn, E. N. (1991). Psychological, biological, and health behavior predictors of blood pressure change in middle-aged women. Journal of Hypertension, 9, 399–406.Google Scholar
Martin, R. A. (2002). Is laughter the best medicine? Humor, laughter, and physical health. Current Directions in Psychological Science, 11(6), 216–220.Google Scholar
McKenna, M. C., Zevon, M. A., Corn, B. & Rounds, I. (1999). Psychosocial factors and the development of cancer: a meta-analysis, Health Psychology, 18, 520–521.Google Scholar
McNair, D., Lorr, M. & Droppleman, L. F. (1971/1981). EITS Manual for the Profile of Mood States. San Diego, CA: Educational and Industrial Testing Service.Google Scholar
Messinger, D. S. (2002). Positive and negative: infant facial expressions and emotions. Current Directions in Psychological Science, 11, 1–6.Google Scholar
Noldus, . (2014). FaceReader: Tool for Automatic Analysis of Facial Expression: Version 6.0 [Software]. Wageningen: Noldus Information Technology B. V.Google Scholar
Papousek, I., Nauschnegg, K., Paechter, M., et al. (2010). Trait and state positive affect and cardiovascular recovery from experimental academic stress. Biological Psychology, 83(2), 108–115.Google Scholar
Parkinson, B., Briner, R. B., Reynolds, S. & Totterdell, P. (1995). Time frames for mood: relations between momentary and generalized ratings of affect. Personality and Social Psychology Bulletin, 21(4), 331–339.Google Scholar
Paterniti, M., Zureik, M., Ducimetiere, P., Feve, J. M. & Alperovitch, A. (2001). Sustained anxiety and 4-year progression of carotid atherosclerosis. Atherosclerosis, Thrombosis and Vascular Biology, 21, 136–141.Google Scholar
Pennix, B. W. J. H., Guralnik, J. M., Pahor, M., et al. (1998). Chronically depressed mood and cancer risk in older persons. Journal of the National Cancer Institute, 90, 1888–1893.Google Scholar
Quigley, K. S., Barrett, L. F. & Weinstein, S. (2002). Cardiovascular patterns associated with threat and challenge appraisals: a within-subjects analysis. Psychophysiology, 39, 292–302.Google Scholar
Radloff, L. S. (1977). The CES-D Scale: a self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401.Google Scholar
Roberts, N. A., Levenson, R. W. & Gross, J. J. (2008). Cardiovascular costs of emotion suppression cross ethnic lines. International Journal of Psychophysiology, 70, 82–87.Google Scholar
Robinson, M. D. & Clore, G. L. (2002). Belief and feeling: evidence for an accessibility model of emotional self-report. Psychological Bulletin, 128(6), 934–960.Google Scholar
Rozanski, A., Blumenthal, J. A. & Kaplan, J. (1999). Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation, 99, 2192–2217.Google Scholar
Rudd, M., Vohs, K. D. & Aaker, J. (2012). Awe expands people’s perception of time and enhances well-being. Psychological Science, 23(10), 1130–1136.Google Scholar
Rude, S. S., Chrisman, J. G., Denmark, A. B. & Maestas, K. L. (2012). Expression of direct anger and hostility predict depression symptoms in formerly depressed women. Canadian Journal of Behavioural Science, 44, 200–209.Google Scholar
Russell, J. A., Bachorowski, J. & Fernandez-Dols, J. (2003). Facial and vocal expressions of emotions. Annual Review of Psychology, 54, 329–349.Google Scholar
Schneiderman, N. (1987). Psychophysiologic factors in atherogenesis and coronary artery disease. Circulation, 76, 141–147.Google Scholar
Shen, B., Eisenberg, S. A., Maeda, U., et al. (2011). Depression and anxiety predict decline in physical health functioning in patients with heart failure. Annals of Behavioral Medicine, 41, 373–382.Google Scholar
Singer, J. A. & Salovey, P. (1988). Mood and memory: evaluating the network theory of affect. Clinical Psychology Review, 8(2), 211–251.Google Scholar
Soto, J. A., Roberts, N. A., Pole, N., Levenson, R. W. & Burleson, M. H. (2012). Elevated baseline anxiety among African Americans in laboratory research settings. Journal of Psychophysiology, 26, 105–115.Google Scholar
Spielberger, C. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
Spielberger, C. (1988). State-Trait Anger Expression Inventory (Revised edn.). Odessa, FL: Psychological Assessment Resources.Google Scholar
Stellar, J. E., John-Henderson, N., Anderson, C. L., et al. (2015). Positive affect and markers of inflammation: discrete positive emotions predict lower levels of inflammatory cytokines. Emotion, 15(2), 129–133.Google Scholar
Steptoe, A. & Wardle, J. (2005). Positive affect and biological function in everyday life. Neurobiology of Aging, 26, S108–S112.Google Scholar
Stewart, J. C., Fitzgerald, G. J. & Kamarck, T. W. (2010). Hostility now, depression later? Longitudinal associations among emotional risk factors for coronary artery disease. Annals of Behavioral Medicine, 39, 258–266.Google Scholar
Taylor, S. E., Kemeny, M. E., Reed, G. M., Bower, J. E. & Gruenewald, T. L. (2000). Psychological resources, positive illusions, and health. American Psychologist, 55, 99–109.Google Scholar
Thomas, D. L. & Diener, E. (1990). Memory accuracy in the recall of emotions. Journal of Personality and Social Psychology, 59(2), 291–297.Google Scholar
Tichon, J. G., Wallis, G., Riek, S. & Mavin, T. (2014). Physiological measurement of anxiety to evaluate performance in simulation training. Cognition, Technology & Work, 16, 203–210.Google Scholar
Tomaka, J., Blascovich, J., Kibler, J. & Ernst, J. M. (1997). Cognitive and physiological antecedents of threat and challenge appraisal. Journal of Personality and Social Psychology, 73, 63–72.Google Scholar
Tugade, M. M. & Fredrickson, B. L. (2004). Resilient individuals use positive emotions to bounce back from negative emotional experiences. Journal of Personality and Social Psychology, 86, 320–333.Google Scholar
Watson, D. & Clark, L. A. (1984). Negative affectivity: the disposition to experience aversive emotional states. Psychological Bulletin, 96(3), 465–490.Google Scholar
Watson, D. & Clark, L. A. (1994). The PANAS-X: Manual for the Positive and Negative Affect Schedule – Expanded Form. Cedar Rapids, IA: University of Iowa.Google Scholar
Watson, D., Clark, L. & Tellegen, A. (1988). Development and validation of a brief measure of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.Google Scholar
Wong, J. M., Sin, N. L. & Whooley, M. A. (2014). A comparison of Cook–Medley hostility subscales and mortality in patients with coronary heart disease: data from the Heart and Soul Study. Psychosomatic Medicine, 76(4), 311–317.Google Scholar
Wood, A. M., Joseph, S., Lloyd, J. & Atkins, S. (2009). Gratitude influences sleep through the mechanism of pre-sleep cognitions. Journal of Psychosomatic Research, 66(1), 43–48.Google Scholar
Zuckerman, B. & Lubin, B. (1985). Manual of Multiple Affect Adjective Check List Revised. San Diego, CA: EdITS.Google Scholar
References
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 Psychiatry Research, 12,189–198.Google Scholar
Krull, K., Scott, J. G. & Sherer, M. (1995). Estimation of premorbid intelligence from combined performance and demographic variables. The Clinical Neuropsychologist, 9, 83–87.Google Scholar
Nasreddine, Z. S., Phillips, N. A., Bedirian, V., et al. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatric Society, 53(4), 695–699. DOI: 10.1111/j.1532–5415.2005.53221.x.Google Scholar
Nelson, H. E. & Willison, J. R. (1991). The Revised National Adult Reading Test: Test Manual. Windsor: NFER-Nelson.Google Scholar
Parson, T. D. (2016). Clinical Neuropsychology and Technology: What’s New and How We Can Use It. Cham: Springer.Google Scholar
Wilkinson, G. S. (1993). WRAT-3: Wide Range Achievement Test Administration Manual (3rd ed.). Wilmington, DE: Western Psychological Services.Google Scholar
References
Apkarian, A. V., Hashmi, J. A. & Baliki, M. N. (2011). Pain and the brain: specificity and plasticity of the brain in chronic pain. Pain, 152, S49–S64.Google Scholar
Bačkonja, M. M. & Farrar, J. T. (2015). Are pain ratings irrelevant? Pain Medicine, 16, 1247–1250.Google Scholar
Baker, S. L. & Kirsch, I. (1991). Cognitive mediators of pain perception and tolerance. Journal of Personality and Social Psychology, 61, 504–510.Google Scholar
Ballantyne, J. C. & Sullivan, M. D. (2015). Intensity of chronic pain: the wrong metric? New England Journal of Medicine, 373, 2098–2099.Google Scholar
Beale, M., Cella, M. & Williams, A. C. de C. (2011). Comparing patients’ and clinician-researchers’ outcome choice for psychological treatment of chronic pain. Pain, 152, 2283–2286.Google Scholar
Birnie, K. A., McGrath, P. J. & Chambers, C. T. (2012). When does pain matter? Acknowledging the subjectivity of clinical significance. Pain, 153, 2311–2314.Google Scholar
Blyth, F. M., March, L. M., Nicholas, M. K. & Cousins, M. J. (2003). Chronic pain, work performance and litigation. Pain, 103, 41–47.Google Scholar
Broderick, J. E., Stone, A. A., Calvanese, P., et al. (2006). Recalled pain ratings: a complex and poorly defined task. Journal of Pain, 7, 142–149.Google Scholar
Cliff, N. & Keats, J. A. (2007). Ordinal Measurement in the Behavioral Sciences. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Cook, K. F., Keefe, F., Jensen, M. P., et al. (2013). Development and validation of a new self-report measure of pain behaviors. Pain, 154, 2867–2876.Google Scholar
Cosco, T. D., Doyle, F., Ward, M. & McGee, H. (2012). Latent structure of the Hospital Anxiety and Depression Scale: a 10-year systematic review. Journal of Psychosomatic Research, 72, 180–184.Google Scholar
Craig, K. D., Prkachin, K. M. & Grunau, R. E. (2011). The facial expression of pain. In Turk, D.C. & Melzack, R. (eds). Handbook of Pain Assessment (3rd edn; pp. 117–133). New York: Guilford Press.Google Scholar
Farrar, J. T., Young, J. P., LaMoureaux, L., et al. (2001). Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale. Pain, 94, 149–158.Google Scholar
Ferreira-Valente, M. A., Pais-Ribeiro, J. L. & Jensen, M. P. (2011). Validity of four pain intensity rating scales. Pain, 152, 2399–3004.Google Scholar
Hadjistavropoulos, T., Breau, L. M. & Craig, K. D. (2011). Assessment of pain in adults and children with limited ability to communicate In Turk, D.C. & Melzack, R. (eds). Handbook of Pain Assessment (3rd edn; pp. 260–280). New York: Guilford Press.Google Scholar
Haggmann, S., Maher, C. G. & Refshauge, K. M. (2004). Screening for symptoms of depression by physical therapists managing low back pain. Physical Therapy, 84, 1157–1166.Google Scholar
Hjermstad, M. J., Fayers, P. M., Haugen, D. F., et al. (2011). Studies comparing numerical rating scales, verbal rating scales, and visual analogue scales for assessment of pain intensity in adults: a systematic literature review. Journal of Pain and Symptom Management, 41, 1073–1093.Google Scholar
Holmberg, C., Karner, J. J., Rappenecker, J. & Witt, C. M. (2014). Clinical trial participants’ experiences of completing questionnaires: a qualitative study. BMJ Open, 4, e004363.Google Scholar
Huijnen, I. P. J., Verbunt, J. A., Peter, M. L., et al. (2011). Differences in activity-related behaviour among patients with chronic low back pain. European Journal of Pain, 15, 748–755.Google Scholar
IASP (International Association for the Study of Pain). (1994). Pain. www.iasp-pain.org/Taxonomy#Pain (accessed 12 October 2016).Google Scholar
IMMPACT (n.d.). Initiative on methods, measurement, and pain assessment in clinical trials. www.immpact.org (accessed 9 October 2016).Google Scholar
Jackson, T., Wang, Y., Wang, Y. & Fan, H. (2014). Self-efficacy and chronic pain: a meta-analytic review. Journal of Pain, 15, 800–814.Google Scholar
Jensen, M. P. & Karoly, P. (2011). Self-report scales and procedures for assessing pain in adults. In Turk, D.C. & Melzack, R. (eds). Handbook of Pain Assessment (3rd edn; pp. 19–44). New York: Guilford Press.Google Scholar
Kappesser, J. & Williams, A. C. de C. (2010). Pain estimation: asking the right questions. Pain, 148, 184–187.Google Scholar
Katz, J. & Melzack, R. (2011). The McGill Pain Questionnaire: development, psychometric properties, and usefulness of the long form, short form, and short form-2. In Turk, D.C. & Melzack, R. (eds). Handbook of Pain Assessment (3rd edn; pp. 45–66). New York: Guilford Press.Google Scholar
Krahé, C., Springer, A., Weinman, J. A. & Fotopoulou, A. (2013). The social modulation of pain: others as predictive signals of salience – a systematic review. Frontiers in Human Neuroscience. DOI: http://dx.doi.org/10.3389/fnhum.2013.00386.Google Scholar
Kroenke, K., Spitzer, R. L. & Williams, J. B. (2003). The Patient Health Questionnaire-2: validity of a two-item depression screener. Medical Care, 41, 1284–1292.Google Scholar
Lints-Martindale, A. C., Hadjistavropoulos, T., Lix, L. M. & Thorpe, L. (2012). A comparative investigation of observational pain assessment tools for older adults with dementia. Clinical Journal of Pain, 28, 226–237.Google Scholar
McCracken, L. M. & Dhingra, L. (2002). A short version of the Pain Anxiety Symptoms Scale (PASS-20): preliminary development and validity. Pain Research and Management, 7, 45–50.Google Scholar
MD Anderson Cancer Center (n.d.). The Brief Pain Inventory. www.mdanderson.org/research/departments-labs-institutes/departments-divisions/symptom-research/symptom-assessment-tools/brief-pain-inventory.html (accessed 9th October 2016).Google Scholar
Melzack, R. (1975). The McGill Pain Questionnaire: major properties and scoring methods. Pain, 1, 277–299.Google Scholar
Michell, J. (2009). The psychometrician’s fallacy: too clever by half. British Journal of Mathematical and Statistical Psychology, 62, 41–55.Google Scholar
Miles, C. L., Pincus, T., Carnes, D., et al. (2011). Measuring pain self-efficacy. Clinical Journal of Pain, 27, 461–470.Google Scholar
Morley, S. J., Williams, A. C. de C. & Black, S. (2002). A confirmatory analysis of the Beck Depression Inventory in chronic pain. Pain, 99, 289–298.Google Scholar
Oosterman, J. M., Zwakhalen, S., Sampson, E. L. & Kunz, M. (2016). The use of facial expressions for pain assessment purposes in dementia: a narrative review. Neurodegenerative Disease Management, 6, 119–131.Google Scholar
Reme, S. E., Lie, S. A. & Eriksen, H. R. (2014). Are 2 questions enough to screen for depression and anxiety in patients with chronic low back pain? Spine, 39, E445–E462.Google Scholar
Schwarz, N. (1999) Self-reports: how the questions shape the answer. American Psychologist, 54, 93–105.Google Scholar
Stinson, J. N., Kavanagh, T., Yamada, J., et al. (2006). Systematic review of the psychometric properties, interpretability and feasibility of self-report pain intensity measures for use in clinical trials with children and adolescents. Pain, 125, 143–157.Google Scholar
Stone, A. A., Schneider, S., Broderick, J. E. & Schwartz, J. E. (2014). Single-day pain assessments as clinical outcomes: not so fast. Clinical Journal of Pain, 30, 739–743.Google Scholar
Sullivan, M. J. L., Bishop, S. R. & Pivik, J. (1995) The Pain Catastrophizing Scale: development and validation. Psychological Assessment, 7, 524–532.Google Scholar
Sullivan, M. J. L., Thorn, B., Haythornthwaite, J. A., et al. (2001) Theoretical perspectives on the relation between catastrophizing and pain. Clinical Journal of Pain, 17, 52–64.Google Scholar
Tan, G., Jensen, M. P., Thornby, J. I. & Shanti, B. F. (2004) Validation of the Brief Pain Inventory for chronic nonmalignant pain. Journal of Pain, 5, 133–137.Google Scholar
Taylor, A. M., Phillips, K., Patel, K. V., et al. (2016). Assessment of physical function and participation in chronic pain clinical trials: IMMPACT/OMERACT recommendations. Pain, 157, 1836–1850.Google Scholar
Tomlinson, D., von Baeyer, C. L., Stinson, J. N. & Sung, L. (2010). A systematic review of faces scales for the self-report of pain intensity in children. Pediatrics, 126, e1168–e1198.Google Scholar
Treister, R., Nielsen, C. S., Stubhaug, A., et al. (2015). Experimental comparison of parametric versus non-parametric analyses of data from the cold pressor test. Journal of Pain, 16, 537–548.Google Scholar
Turk, D.C. & Melzack, R (eds) (2011). Handbook of Pain Assessment (3rd edn). New York: Guilford Press.Google Scholar
Williams, A. C. de C. (2002). Facial expression of pain: an evolutionary account. Behavioural and Brain Sciences, 25, 439–488.Google Scholar
Williams, A. C. de C. & Craig, K. D. (2016). Updating the definition of pain. Pain. 157, 2420–2423.Google Scholar
Williams, A. C. de C., Davies, H. T. O. & Chadury, Y. (2000). Simple pain rating scales hide complex idiosyncratic meanings. Pain, 85, 457–463.Google Scholar
Zigmond, A. S. & Snaith, R. P. (1983) The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica, 67, 361–370.Google Scholar
References
Alonso, J, Bartlett, SJ, Rose, M, et al. (2013). The case for an international patient-reported outcomes measurement information system (PROMIS®) initiative. Health and Quality of Life Outcomes. 11:210.Google Scholar
Beck, A. T., Steer, R. A., Ball, R. & Ranieri, W. (1996). Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. Journal of Personality Assessment, 67(3),588–597.Google Scholar
Bergner, M., Bobbitt, R. A., Carter, W. B., et al. (1981).The Sickness Impact Profile: development and final revision of a health status measure. Medical Care, 19(8), 787–805.Google Scholar
Black, N., Burke, L., Forrest, C. B., et al.(2016). Patient-reported outcomes: pathways to better health, better services, and better societies. Quality of Life Research, 25(5),1103–1112.Google Scholar
Boyce, M. B., Browne, J. P. & Greenhalgh, J. (2014). The experiences of professionals with using information from patient-reported outcome measures to improve the quality of healthcare: a systematic review of qualitative research. BMJ Quality and Safety, 23(6), 508–518.Google Scholar
Calvert, M., Brundage, M., Jacobsen, P. B., et al. (2013).The CONSORT Patient-Reported Outcome (PRO) extension: implications for clinical trials and practice. Health and Quality of Life Outcomes, 11, 184.Google Scholar
Clark, D. M. (2011). Implementing NICE guidelines for the psychological treatment of depression and anxiety disorders: the IAPT experience. International Review of Psychiatry, 23(4),318–327.Google Scholar
Demyttenaere, K., Bruffaerts, R., Posada-Villa, J., et al. (2004). Prevalence, severity, and unmet need for treatment of mental disorders in the World Health Organization World Mental Health Surveys. JAMA, 291(21), 2581–2590.Google Scholar
Emery, M. P., Perrier, L. L. & Acquadro, C. (2005). Patient-Reported Outcome and Quality of Life Instruments Database (PROQOLID): frequently asked questions. Health and Quality of Life Outcomes, 3, 12.Google Scholar
Espallargues, M., Valderas, J. M. & Alonso, J. (2000). Provision of feedback on perceived health status to health care professionals: a systematic review of its impact. Medical Care, 38(2), 175–186.Google Scholar
Fischer, F., Gibbons, C., Coste, J., et al, (2018). Measurement invariance and general population reference values of the PROMIS Profile 29 in the UK, France, and Germany. Quality of Life Research, 27(6), 1–16.Google Scholar
Garcia-Duran Huet, M., Ferrer, M., Herdman, M. J., et al. (2010). BiblioPRO: online library of PRO instruments in Spanish. Quality of Life Research, 19, 62–63.Google Scholar
Gilbody, S. M., House, A. O. & Sheldon, T. A. (2001). Routine administered questionnaires for depression and anxiety: systematic review. British Medical Journal. 322, 406–409.Google Scholar
Goldberg, D. & Williams, P. (2006). A User’s Guide to the General Health Questionnaire. London: GL Assessment.Google Scholar
Gonçalves Bradley, D. C., Gibbons, C., Ricci-Cabello, I., et al. (2015). Routine provision of information on patient-reported outcome measures to healthcare providers and patients in clinical practice. Cochrane Database of Systematic Reviews, 3, CD011589. DOI: 10.1002/14651858.CD011589.Google Scholar
Greenhalgh, J. (2009) The applications of PROs in clinical practice: what are they, do they work, and why? Quality of Life Research, 18(1), 115–123.Google Scholar
Greenhalgh, J. & Meadows, K. (1999). The effectiveness of the use of patient-based measures of health in routine practice in improving the process and outcomes of patient care: a literature review. Journal of Evaluation in Clinical Practice, 5(4):401–416.Google Scholar
Greenhalgh, J., Dalkin, S., Gooding, K., et al. (2017). Functionality and feedback: a realist synthesis of the collation, interpretation and utilisation of patient-reported outcome measures data to improve patient care. Southampton (UK), NIHR Journals Library.Google Scholar
Kendrick, T., El-Gohary, M., Stuart, B., et al. (2016). Routine use of patient reported outcome measures (PROMs) for improving treatment of common mental health disorders in adults. Cochrane Database of Systematic Reviews, 7, CD011119. DOI: 10.1002/14651858.CD011119.pub2.Google Scholar
Knaup, C., Koesters, M., Schoefer, D., et al. (2009). Effect of feedback of treatment outcome in specialist mental healthcare: meta-analysis. British Journal of Psychiatry, 195, 15–22.Google Scholar
Kroenke, K., Spitzer, R. L. & Williams, J. B. (2001). The PHQ‐9. Journal of General Internal Medicine, 16(9): 606–613.Google Scholar
Lawton, M. P. & Brody, E. M. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. The Gerontologist, 9(3), 179–186.Google Scholar
Marshall, S., Haywood, K. & Fitzpatrick, R. (2006). Impact of patient reported outcome measures on routine practice: a structured review. Journal of Evaluation in Clinical Practice, 12(5), 559–568.Google Scholar
Mokkink, L. B., Terwee, C. B., Patrick, D. L., et al. (2010). The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. Journal of Clinical Epidemiology, 63(7), 737–745.Google Scholar
National Health Interview Survey (2014). Survey description. Centers for Disease Control and Prevention. www.cdc.gov/nchs/nhis/quest_data_related_1997_forward.htm (accessed 20 November 2016).Google Scholar
O’Boyle, C. (1994). The schedule for the evaluation of individual quality of life (SEIQOL). International Journal of Mental Health, 23(3), 3–23.Google Scholar
Porter, I., Gonçalves-Bradley, D., Ricci-Cabello, I., et al. (2016). Framework and guidance for implementing patient-reported outcomes in clinical practice: evidence, challenges and opportunities. Journal of Comparative Effectiveness Research, 5(5), 507–519.Google Scholar
Rabin, R. & de Charro, F. (2001). EQ-5D: a measure of health status from the EuroQol Group. Annals of Medicine, 33(5), 337–343.Google Scholar
Ruta, D. A., Garratt, A. M., Leng, M., et al. (1994). A new approach to the measurement of quality of life: the patient-generated index. Medical Care, 32(11), 1109–1126.Google Scholar
Snyder, C. F., Aaronson, N. K., Choucair, A. K., et al. (2012). Implementing patient-reported outcomes assessment in clinical practice: a review of the options and considerations. Quality of Life Research, 21(8), 1305–1314.Google Scholar
Spitzer, R. L, Kroenke, K., Williams, J. B., Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine, 166(10): 1092–1097.Google Scholar
Unsworth, G., Cowie, H. & Green, A.(2012). Therapists’ and clients’ perceptions of routine outcome measurement in the NHS: a qualitative study. Counselling and Psychotherapy Research, 12(1), 71–80.Google Scholar
US Food and Drug Administration. (2006). Guidance for industry patient-reported outcome measures: use in medical product development to support labeling claims. www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM193282.pdf (accessed 20 November 2016).Google Scholar
Valderas, J. M., Ferrer, M., Mendívil, J., et al. (2008a). Development of EMPRO: a tool for the standardized assessment of patient-reported outcome measures. Value in Health, 11(4), 700–708.Google Scholar
Valderas, J. M., Kotzeva, A., Espallargues, M., et al. (2008b). The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature. Quality of Life Research, 17(2), 179–193.Google Scholar
Valderas, J. M., Espallargues, M., Kotzeva, A., et al. (2010). Assessing the impact of routinely measuring patient-reported outcomes in clinical practice: critical appraisal of 34 randomized clinical trials. Quality of Life Research, 17(1), 11Google Scholar
Van der Linden, W.J. & Glas, A.W.G. (eds) (2000). Computerized Adaptive Testing: Theory and Practice. Dordrecht: Kluwer Academic.Google Scholar
Ware, J. E., Kosinski, M. & Gandek, B. (2000) SF-36 Health Survey: Manual and Interpretation Guide. Lincoln, RI: Quality Metric Inc.Google Scholar
Zung, W. W. K. (1965). A self rating depression rating scale. Archives of General Psychiatry, 12, 63–70.Google Scholar
References
Breen, E. C., Reynolds, S. M., Cox, C., et al. (2011). Multisite comparison of high-sensitivity multiplex cytokine assays. Clinical and Vaccine Immunology, 18(8), 1229–1242.Google Scholar
Broadbent, E., Petrie, K., Alley, P. & Booth, R. (2003). Psychological stress impairs early wound repair following surgery. Psychosomatic Medicine, 65(5), 865–869.Google Scholar
Brookout, A. L., Cummins, C. L., Kramer, M. F., Pesola, J. M. & Mangelsdorf, D. J. (2006). High-throughput real-time quantitative reverse transcription PCR. Current Protocols in Molecular Biology, 15(8). DOI: 10.1002/0471142727.mb1508s73.Google Scholar
Burns, V. E., Carroll, D., Ring, C. & Drayson, M. (2003). Antibody response to vaccination and psychosocial stress in humans: relationships and mechanisms. Vaccine, 21(19–20), 2523–2534.Google Scholar
Christian, L. M., Graham, J. E., Padgett, D. A., Glaser, R. & Kiecolt-Glaser, J. K. (2007). Stress and wound healing. NeuroImmunoModulation, 13(5–6), 337–346.Google Scholar
Cohen, S., Tyrrell, D. A. & Smith, A. P. (1993). Negative life events, perceived stress, negative affect, and susceptibility to the common cold. Journal of Personality and Social Psychology, 64(1), 131–140.Google Scholar
Cohen, S., Doyle, W. J., Skoner, D. P., Rabin, B. S. & Gwaltney, J. M. (1997). Social ties and susceptibility to the common cold. JAMA, 277(24), 1940–1944.Google Scholar
Cole, S. W., Yan, W., Galic, Z., Arevalo, J. & Zack, J. A. (2005). Expression-based monitoring of transcription factor activity: the TELiS database. Bioinformatics, 21(6), 803–810.Google Scholar
Elshal, M. F. & McCoy, J. P. (2006). Multiplex bead array assays: performance evaluation and comparison of sensitivity to ELISA. Methods, 38(4), 317–323.Google Scholar
Graham-Engeland, J. E., Engeland, C. G. Sin, N. L., et al. (2016). The relationship between mood and inflammatory biomarkers is influenced by their temporal proximity and mood measurement. Presentation at the Psychoneuroimmunology Research Society, Brighton, UK.Google Scholar
Mandala, W. L., Ananworanich, J., Apornpong, T., et al. (2014). Control lymphocyte subsets: can one country’s values serve for another’s? Journal of Allergy and Clinical Immunology, 134(3), 7–10.Google Scholar
Marsland, A. L., Herbert, T. B., Muldoon, M. F., et al. (1997). Lymphocyte subset redistribution during acute laboratory stress in young adults: mediating effects of hemoconcentration. Health Psychology, 16(4), 341–348.Google Scholar
Miller, G. E., Chen, E. & Parker, K. J. (2011). Psychological stress in childhood and susceptibility to the chronic diseases of aging: moving toward a model of behavioral and biological mechanisms. Psychological Bulletin, 137(6), 959–997.Google Scholar
O’Connor, M. F., Bower, J. E., Cho, H. J., et al. (2009). To assess, to control, to exclude: effects of biobehavioral factors on circulating inflammatory markers. Brain, Behavior, and Immunity, 23(7), 887–897.Google Scholar
Papanicolaou, D. A., Wilder, R. L., Manolagas, S. C. & Chrousos, G. P. (1998). The pathophysiologic roles of interleukin-6 in human disease. Annals of Internal Medicine, 128(2), 127–137.Google Scholar
Segerstrom, S. C. & Miller, G. E. (2004). Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. Psychological Bulletin, 130(4), 601–630.Google Scholar
Smith, A., Vollmer-Conna, U., Bennett, B., et al. (2004). The relationship between distress and the development of a primary immune response to a novel antigen. Brain, Behavior, and Immunity, 18(1), 65–75.Google Scholar
Van Loveren, H., Van Amsterdam, J. G. C., Vandebriel, R. J., et al. (2001). Vaccine-induced antibody responses as parameters of the influence of endogenous and environmental factors. Environmental Health Perspectives, 109(8), 757–764.Google Scholar
Zhou, X., Fragala, M. S., McElhaney, J. E. & Kuchel, G. A. (2010). Conceptual and methodological issues relevant to cytokine and inflammatory marker measurements in clinical research. Current Opinion in Clinical Nutrition & Metabolic Care, 13(5), 541–547.Google Scholar
References
Abdul-Halim, A. A. (1982). Social support and managerial affective responses to job stress. Journal of Occupational Behavior, 3, 281–295Google Scholar
Aguilera, R. V. (2005). Corporate governance and director accountability: an institutional comparative perspective. British Journal of Management, 16(suppl. 1), S39–S53.Google Scholar
Amato, P. R. & Hohmann‐Marriott, B. (2007). A comparison of high‐and low‐distress marriages that end in divorce. Journal of Marriage and Family, 69(3), 621–638.Google Scholar
Aneshensel, C. S. & Frerichs, R. R. (1982). Stress, support, and depression: a longitudinal causal model. Journal of Community Psychology, 10(4), 363–376.Google Scholar
Antonucci, T. C. & Akiyama, H. (1987). Social networks in adult life and a preliminary examination of the convoy model. Journal of Gerontology, 42(5), 519–527.Google Scholar
Barger, S. D. (2013). Social integration, social support and mortality in the US National Health Interview Survey. Psychosomatic Medicine, 75(5), 510–517.Google Scholar
Barrera, M. (1986). Distinctions between social support concepts, measures, and models. American Journal of Community Psychology, 14(4), 413–445.Google Scholar
BarreraJr, M. (2000). Social support research in community psychology. In Handbook of Community Psychology (pp. 215–245). New York: Springer.Google Scholar
Baron, R. M. & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173.Google Scholar
Bergeman, C. S., Neiderhiser, J. M., Pedersen, N. L. & Plomin, R. (2001). Genetic and environmental influences on social support in later life: a longitudinal analysis. The International Journal of Aging and Human Development, 53(2), 107–135.Google Scholar
Berkman, L. F. & Glass, T. (2000). Social integration, social networks, social support, and health. Social Epidemiology 1, 137–173.Google Scholar
Berkman, L. F., Glass, T., Brissette, I. & Seeman, T. E. (2000). From social integration to health: Durkheim in the new millennium. Social Science & Medicine, 51(6), 843–857.Google Scholar
Bickart, K. C., Hollenbeck, M. C., Barrett, L. F. & Dickerson, B. C. (2012). Intrinsic amygdala–cortical functional connectivity predicts social network size in humans. Journal of Neuroscience, 32(42), 14729–14741.Google Scholar
Bolger, N. & Amarel, D. (2007). Effects of social support visibility on adjustment to stress: experimental evidence. Journal of Personality and Social Psychology, 92(3), 458.Google Scholar
Bolger, N., Zuckerman, A. & Kessler, R. C. (2000). Invisible support and adjustment to stress. Journal of Personality and Social Psychology, 79(6), 953.Google Scholar
Bourdieu, P. (1985). The social space and the genesis of groups. Information (International Social Science Council), 24(2), 195–220.Google Scholar
Burt, R. S. (2000). The network structure of social capital. Research in Organizational Behavior, 22, 345–423.Google Scholar
Button, D. M., O’Connell, D. J. & Gealt, R. (2012). Sexual minority youth victimization and social support: the intersection of sexuality, gender, race, and victimization. Journal of Homosexuality, 59(1), 18–43.Google Scholar
Chak, A. (1996). Conceptualizing social support: a micro or macro perspective?. プシコロギア, 東洋国際心理学誌, 39(2), 74–83.Google Scholar
Chou, C. C. & Chronister, J. A. (2012). Social tie characteristics and psychiatric rehabilitation outcomes among adults with serious mental illness. Rehabilitation Counseling Bulletin, 55(2), 92–102.Google Scholar
Chronister, J., Chou, C. C., Frain, M. & da Silva Cardoso, E. (2008). The relationship between social support and rehabilitation related outcomes: a meta-analysis. Journal of Rehabilitation, 74(2), 16.Google Scholar
Chronister, J., Chou, C. C. & Liao, H. Y. (2013). The role of stigma coping and social support in mediating the effect of societal stigma on internalized stigma, mental health recovery, and quality of life among people with serious mental illness. Journal of Community Psychology, 41(5), 582–600.Google Scholar
Cohen, S. & Lemay, E. P. (2007). Why would social networks be linked to affect and health practices? Health Psychology, 26(4), 410.Google Scholar
Cohen, S. & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310.Google Scholar
Cohen, S., Gottlieb, B. H. & Underwood, L. G. (2001). Social relations and health: challenges for measurement and intervention. Advances in Mind–Body Medicine, 17, 129–141.Google Scholar
Cohen, S., Janicki-Deverts, D., Turner, R. B. & Doyle, W. J. (2015). Does hugging provide stress-buffering social support? A study of susceptibility to upper respiratory infection and illness. Psychological Science, 26(2), 135–147.Google Scholar
Cutrona, C. E. & Russell, D. W. (1990). Type of social support and specific stress: toward a theory of optimal matching. In Sarason, B. R., Sarason, I. G. & Pierce, G. R. (eds), Social Support: An Interactional View (pp. 319–366). Oxford: John WileyGoogle Scholar
Davern, M. & Hachen, D. S. (2006). The role of information and influence in social networks. American Journal of Economics and Sociology, 65(2), 269–293.Google Scholar
Ditzen, B., Neumann, I. D., Bodenmann, G., et al. (2007). Effects of different kinds of couple interaction on cortisol and heart rate responses to stress in women. Psychoneuroendocrinology, 32(5), 565–574.Google Scholar
Dohrenwend, B. S., Dohrenwend, B. P., Dodson, M. & Shrout, P. E. (1984). Symptoms, hassles, social supports, and life events: problem of confounded measures. Journal of Abnormal Psychology, 93(2), 222.Google Scholar
Donath, J. & Boyd, D. (2004). Public displays of connection. BT Technology Journal, 22(4), 71–82.Google Scholar
Dunkel-Schetter, C. & Bennett, T. L. (1990). Differentiating the cognitive and behavioral aspects of social support. In Sarason, B. R., Sarason, I. G. & Pierce, G. R. (eds), Social Support: An Interactional View (pp. 267–296). Oxford: John WileyGoogle Scholar
Durkheim, E. (1951 [1897]). Suicide: a Study in Sociology. Translated by Spaulding, J. A. and Simpson, G.. Glencoe, IL: The Free Press.Google Scholar
Ferlander, S. (2007). The importance of different forms of social capital for health. Acta Sociologica, 50(2), 115–128.Google Scholar
Fernandez, R. M., Castilla, E. J. & Moore, P. (2000). Social capital at work: networks and employment at a phone center. American Journal of Sociology, 105(5), 1288–1356.Google Scholar
Fowler, J. H. & Christakis, N. A. (2008). Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. BMJ, 337, a2338.Google Scholar
Frazier, P. A., Tix, A. P. & Barnett, C. L. (2003). The relational context of social support: relationship satisfaction moderates the relations between enacted support and distress. Personality and Social Psychology Bulletin, 29(9), 1133–1146.Google Scholar
Furukawa, T. & Shibayama, T. (1997). Intra-individual versus extra-individual components of social support. Psychological Medicine, 27(5), 1183–1191.Google Scholar
Gittell, R. & Vidal, A. (1998). Community Organizing: Building Social Capital as a Development Strategy. New York: Sage.Google Scholar
Gleason, M. E., Iida, M., Shrout, P. E. & Bolger, N. (2008). Receiving support as a mixed blessing: evidence for dual effects of support on psychological outcomes. Journal of Personality and Social Psychology, 94(5), 824.Google Scholar
Gore, S. (1981). Stress-buffering functions of social supports: an appraisal and clarification of research models. In Dohrenwend, B. (ed), Stressful Life Events and Their Contexts, pp. (202–222). New Brunswick, NJ: Rutgers University Press.Google Scholar
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.Google Scholar
Granovetter, M. (1985). Economic action and social structure: the problem of embeddedness. American Journal of Sociology, 91(3), 481–510.Google Scholar
Grewen, K. M., Anderson, B. J., Girdler, S. S. & Light, K. C. (2003). Warm partner contact is related to lower cardiovascular reactivity. Behavioral Medicine, 29(3), 123–130.Google Scholar
Hamrick, N., Cohen, S. & Rodriguez, M. S. (2002). Being popular can be healthy or unhealthy: stress, social network diversity, and incidence of upper respiratory infection. Health Psychology, 21(3), 294.Google Scholar
Helgeson, V. S. (1993). Two important distinctions in social support: kind of support and perceived versus received. Journal of Applied Social Psychology, 23(10), 825–845.Google Scholar
Helgeson, V. S. & Cohen, S. (1996). Social support and adjustment to cancer: reconciling descriptive, correlational, and intervention research. Health Psychology, 15(2), 135.Google Scholar
Heller, K., Swindle, R. W. & Dusenbury, L. (1986). Component social support processes: comments and integration. Journal of Consulting and Clinical Psychology, 54(4), 466.Google Scholar
Henderson, S., Byrne, D. G. & Duncan-Jones, P. (1981). Neurosis and the Social Environment. London: Academic Press.Google Scholar
Holt-Lunstad, J., Birmingham, W. A. & Light, K. C. (2008). Influence of a ‘warm touch’ support enhancement intervention among married couples on ambulatory blood pressure, oxytocin, alpha amylase, and cortisol. Psychosomatic Medicine, 70(9), 976–985.Google Scholar
House, J. S., Kahn, R. L., McLeod, J. D. & Williams, D. (1985). Measures and concepts of social support. In Cohen, S. & Syme, S. L. (eds), Social Support and Health (pp. 83–108). San Diego, CA: Academic Press.Google Scholar
Iyer, S., Kitson, M. & Toh, B. (2005). Social capital, economic growth and regional development. Regional Studies, 39(8), 1015–1040.Google Scholar
Kaufmann, G. M. & Beehr, T. A. (1986). Interactions between job stressors and social support: some counterintuitive results. Journal of Applied Psychology, 71(3), 522.Google Scholar
Kawachi, I. & Berkman, L. F. (2001). Social ties and mental health. Journal of Urban Health, 78(3), 458–467.Google Scholar
Kim, H. S. (2015). Exploring the downside of social embeddedness: evidence from a cross‐national study. Social Science Quarterly. DOI: 10.1111/ssqu.12231.Google Scholar
Lakey, B. & Cassady, P. B. (1990). Cognitive processes in perceived social support. Journal of Personality and Social Psychology, 59(2), 337.Google Scholar
Lancee, B. (2012). The economic returns of bonding and bridging social capital for immigrant men in Germany. Ethnic and Racial Studies, 35(4), 664–683.Google Scholar
Lin, N. & Dumin, M. (1986). Access to occupations through social ties. Social Networks, 8(4), 365–385.Google Scholar
Lin, N., Woelfel, M. W. & Light, S. C. (1985). The buffering effect of social support subsequent to an important life event. Journal of Health and Social Behavior, 26, 247–263.Google Scholar
Mahon, N. E. & Yarcheski, A. (2017). Parent and friend social support and adolescent hope. Clinical Nursing Research, 26(2), 224–240.Google Scholar
Master, S. L., Eisenberger, N. I., Taylor, S. E., et al. (2009). A picture’s worth: partner photographs reduce experimentally induced pain. Psychological Science, 20(11), 1316–1318.Google Scholar
Martire, L. M., Stephens, M. A. P., Druley, J. A. & Wojno, W. C. (2002). Negative reactions to received spousal care: predictors and consequences of miscarried support. Health Psychology, 21(2), 167.Google Scholar
Molesworth, T., Sheu, L. K., Cohen, S., Gianaros, P. J. & Verstynen, T. D. (2015). Social network diversity and white matter microstructural integrity in humans. Social Cognitive and Affective Neuroscience, 10(9), 1169–1176.Google Scholar
Narayan, D. & Pritchett, L. (1997). Cents and sociability: Household income and social capital in rural Tanzania. World Bank Research Working Paper No. 1796.Google Scholar
Nie, N. H. (2001). Sociability, interpersonal relations, and the Internet: reconciling conflicting findings. American Behavioral Scientist, 45(3), 420–435.Google Scholar
Nyqvist, F., Pape, B., Pellfolk, T., Forsman, A. K. & Wahlbeck, K. (2014). Structural and cognitive aspects of social capital and all-cause mortality: a meta-analysis of cohort studies. Social Indicators Research, 116(2), 545–566.Google Scholar
Pierce, G. R., Lakey, B., Sarason, I. G., Sarason, B. R. & Joseph, H. J. (1997). Personality and social support processes. In Pierce, G. R., Lakey, B. & Sarason, I. G. (eds), Sourcebook of Social Support and Personality (pp. 3–18). New York: Springer.Google Scholar
Polanyi, K. (1944). The Great Transformation: The Political and Economic Origins of Our Time. New York: Rinehart & Company.Google Scholar
Polanyi, K. (1957). The economy as instituted process. In Polanyi, K., Arensberg, C.M. & Pearson, H.W. (eds), Trade and Market in the Early Empires: Economies in History and Theory (pp. 243–270). New York: Free Press.Google Scholar
Portes, A. (1998). Social capital: its origins and applications in modern sociology. Annual Review of Sociology, 24(1), 1–24.Google Scholar
Portes, A. & Mooney, M. (2002). Social capital and community development. In Meyer, M., Guillen, M., Collins, R. & England, P. (eds), The New Economic Sociology: Development in an Emerging Field (pp. 303–329). New York: Russell Sage Foundation.Google Scholar
Prati, G. & Pietrantoni, L. (2009). Optimism, social support, and coping strategies as factors contributing to posttraumatic growth: a meta-analysis. Journal of Loss and Trauma, 14(5), 364–388.Google Scholar
Putnam, R. D. (2000). Bowling alone: America’s declining social capital. In Crothers, L. & Lockhart, C. (eds) Culture and Politics (pp. 223–234). New York: Palgrave Macmillan.Google Scholar
Rook, K. S. & Pietromonaco, P. (1987). Close relationships: ties that heal or ties that bind. Advances in Personal Relationships, 1, 1–35.Google Scholar
Sampson, R. J., Morenoff, J. D. & Earls, F. (1999). Beyond social capital: spatial dynamics of collective efficacy for children. American Sociological Review, 64, 633–660.Google Scholar
Sapag, J. C., Aracena, M., Villarroel, L., et al. (2008). Social capital and self-rated health in urban low income neighbourhoods in Chile. Journal of Epidemiology and Community Health, 62(9), 790–792.Google Scholar
Sarason, B. R., Sarason, I. G. & Pierce, G. R. (1990). Social Support: An Interactional View. Chichester: John Wiley & Sons.Google Scholar
Sarason, B. R., Pierce, G. R., Shearin, E. N., et al. (1991). Perceived social support and working models of self and actual others. Journal of Personality and Social Psychology, 60(2), 273.Google Scholar
Schachter, S. (1959). The Psychology of Affiliation. Stanford, CA: Stanford University Press.Google Scholar
Schuller, T. (2000). Social and human capital: the search for appropriate technomethodology. Policy Studies, 21(1), 25–35.Google Scholar
Shumaker, S. A. & Brownell, A. (1984). Toward a theory of social support: closing conceptual gaps. Journal of Social Issues, 40(4), 11–36.Google Scholar
Shumaker, S. A. & Hill, D. R. (1991). Gender differences in social support and physical health. Health Psychology, 10(2), 102.Google Scholar
Szreter, S. (2000). Social capital, the economy, and education in historical perspective. In Baron, S., Field, J. & Schuller, T. (eds), Social Capital: Critical Perspectives (pp. 56–77). Oxford: Oxford University Press.Google Scholar
Szreter, S. & Woolcock, M. (2004). Health by association? Social capital, social theory, and the political economy of public health. International Journal of Epidemiology, 33(4), 650–667.Google Scholar
Thoits, P. A. (1986). Social support as coping assistance. Journal of Consulting and Clinical Psychology, 54(4), 416.Google Scholar
Thoits, P. A. (1992). Identity structures and psychological well-being: gender and marital status comparisons. Social Psychology Quarterly, 55, 236–256.Google Scholar
Thoits, P. A. (1995). Stress, coping, and social support processes: Where are we? What next? Journal of Health and Social Behavior, 35, 53–79.Google Scholar
Thoits, P. A. (2011). Mechanisms linking social ties and support to physical and mental health. Journal of Health and Social Behavior, 52(2), 145–161.Google Scholar
Thorsteinsson, E. B. & James, J. E. (1999). A meta-analysis of the effects of experimental manipulations of social support during laboratory stress. Psychology and Health, 14(5), 869–886.Google Scholar
Tsai, A. C., Lucas, M. & Kawachi, I. (2015). Association between social integration and suicide among women in the United States. JAMA Psychiatry, 72(10), 987–993.Google Scholar
Uchino, B. N. (2004). Social Support and Physical Health: Understanding the Health Consequences of Relationships. New Haven, CT: Yale University Press.Google Scholar
Umberson, D. (1987). Family status and health behaviors: social control as a dimension of social integration. Journal of Health and Social Behavior, 28, 306–319.Google Scholar
Umberson, D. & Karas Montez, J. (2010). Social relationships and health: a flashpoint for health policy. Journal of Health and Social Behavior, 51(Suppl. 1), S54–S66.Google Scholar
Uslaner, E. M. & Conley, R. S. (2003). Civic engagement and particularized trust: the ties that bind people to their ethnic communities. American Politics Research, 31(4), 331–360.Google Scholar
Viswesvaran, C., Sanchez, J. I. & Fisher, J. (1999). The role of social support in the process of work stress: a meta-analysis. Journal of Vocational Behavior, 54(2), 314–334.Google Scholar
Wasserman, S.