Conceptualization, Measurement, and Analysis of Negative Affective Risk Factors

Smith, Timothy W.

doi:10.1007/978-0-387-09488-5_12

Cited by 14 publications

(9 citation statements)

References 61 publications

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“…Furthermore, claims that prognostic value of Type D personality is independent of depressive symptoms should be greeted with skepticism, given the long-recognized high association among measures of negative affect [40][41][42][43][44]. Seemingly reasonable theoretical and conceptual distinctions often cannot be sustained when attempts are made to demonstrate discriminant validity of measures of specific negative affects.…”

Section: Meta-analysis To the Rescue?mentioning

confidence: 99%

Are we witnessing the decline effect in the Type D personality literature? What can be learned?

Coyne¹,

Voogd²

2012

Journal of Psychosomatic Research

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a b s t r a c t a r t i c l e i n f oAfter an unbroken series of positive, but underpowered studies seemed to demonstrate Type D personality predicting mortality in cardiovascular disease patients, initial claims now appear at least exaggerated and probably false. Larger studies with consistently null findings are accumulating. Conceptual, methodological, and statistical issues can be raised concerning the construction of Type D personality as a categorical variable, whether Type D is sufficiently distinct from other negative affect variables, and if it could be plausibly assumed to predict mortality independent of depressive symptoms and known biomedical factors, including disease severity. The existing literature concerning negative affect and health suggests a low likelihood of discovering a new negative affect variable that independently predicts mortality better than its many rivals. The apparent decline effect in the Type D literature is discussed in terms of the need to reduce the persistence of false positive findings in the psychosomatic medicine literature, even while preserving a context allowing risk-taking and discovery. Recommendations include greater transparency concerning research design and analytic strategy; insistence on replication with larger samples before accepting "discoveries" from small samples; reduced confirmatory bias; and availability of all relevant data. Such changes would take time to implement, face practical difficulties, and run counter to established practices. An interim solution is for readers to maintain a sense of pre-discovery probabilities, to be sensitized to the pervasiveness of the decline effect, and to be skeptical of claims based on findings reaching significance in small-scale studies that have not been independently replicated.© 2012 Elsevier Inc. All rights reserved. IntroductionMany "discoveries" turn out to be exaggerated or simply false across diverse research areas and disciplines. John Ioannidis [1] provoked concern with his demonstration that of the 49 most cited clinical research studies in major journals, replications of 34 had been attempted, and 41% of key findings had been refuted or shown to be substantially diminished. In a subsequent paper [2] he offered evidence that "most claimed research findings are false" and he and others [3-6] have since identified some mechanisms by which discoveries appear in the literature and then undergo a decline or refutation. Claims of breakthrough discoveries frequently arise in small positive studies that would seem to be too underpowered to detect an effect, and the inadequate sample size makes findings all the more attention grabbing.Yet, portrayals in the literature of such "discoveries" ignore the larger context of a strong confirmatory bias in published research papers, with unknown numbers of negative findings not being published and findings being declared discoveries simply because of having achieved an arbitrary level of significance. Moreover, statistically significant findings in small studies are nece...

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Section: Meta-analysis To the Rescue?mentioning

confidence: 99%

Are we witnessing the decline effect in the Type D personality literature? What can be learned?

Coyne¹,

Voogd²

2012

Journal of Psychosomatic Research

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“…negative affect, shared diagnostic symptoms and artificial diagnostic splitting). Although the extent of overlap between psychosocial constructs in CHD has long been highlighted as crucial to define (Kubzansky et al, 2006;Kubzansky and Kawachi, 2000;Smith, 2010); Suls and Bunde, 2005;Tully et al, 2008), we are not aware of a previous study to pool such data together and thereby quantify the association between depression and anxiety in CHD patients.…”

Section: Introductionmentioning

confidence: 99%

Generalized anxiety disorder prevalence and comorbidity with depression in coronary heart disease: A meta-analysis

Tully

Cosh

2013

J Health Psychol

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Generalized anxiety disorder prevalence and comorbidity with depression in coronary heart disease patients remain unquantified. Systematic searching of Medline, Embase, SCOPUS and PsycINFO databases revealed 1025 unique citations. Aggregate generalized anxiety disorder prevalence (12 studies, N = 3485) was 10.94 per cent (95% confidence interval: 7.8-13.99) and 13.52 per cent (95% confidence interval: 8.39-18.66) employing Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria (random effects). Lifetime generalized anxiety disorder prevalence was 25.80 per cent (95% confidence interval: 20.84-30.77). In seven studies, modest correlation was evident between generalized anxiety disorder and depression, Fisher's Z = .30 (95% confidence interval: .19-.42), suggesting that each psychiatric disorder is best conceptualized as contributing unique variance to coronary heart disease prognosis.

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“…fear) and depression and related constructs (e.g. helplessness) [ 12 ]. Therefore, MI-related fear of dying and helplessness could be understood as part of the negative affective spectrum being associated with poor cardiovascular prognosis in the aftermath of MI.…”

Section: Introductionmentioning

confidence: 99%

Distress related to myocardial infarction and cardiovascular outcome: a retrospective observational study

et al. 2011

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BackgroundDuring acute coronary syndromes patients perceive intense distress. We hypothesized that retrospective ratings of patients' MI-related fear of dying, helplessness, or pain, all assessed within the first year post-MI, are associated with poor cardiovascular outcome.MethodsWe studied 304 patients (61 ± 11 years, 85% men) who after a median of 52 days (range 12-365 days) after index MI retrospectively rated the level of distress in the form of fear of dying, helplessness, or pain they had perceived at the time of MI on a numeric scale ranging from 0 ("no distress") to 10 ("extreme distress"). Non-fatal hospital readmissions due to cardiovascular disease (CVD) related events (i.e., recurrent MI, elective and non-elective stent implantation, bypass surgery, pacemaker implantation, cerebrovascular incidents) were assessed at follow-up. The relative CVD event risk was computed for a (clinically meaningful) 2-point increase of distress using Cox proportional hazard models.ResultsDuring a median follow-up of 32 months (range 16-45), 45 patients (14.8%) experienced a CVD-related event requiring hospital readmission. Greater fear of dying (HR 1.21, 95% CI 1.03-1.43), helplessness (HR 1.22, 95% CI 1.04-1.44), or pain (HR 1.27, 95% CI 1.02-1.58) were significantly associated with an increased CVD risk without adjustment for covariates. A similarly increased relative risk emerged in patients with an unscheduled CVD-related hospital readmission, i.e., when excluding patients with elective stenting (fear of dying: HR 1.26, 95% CI 1.05-1.51; helplessness: 1.26, 95% CI 1.05-1.52; pain: HR 1.30, 95% CI 1.01-1.66). In the fully-adjusted models controlling for age, the number of diseased coronary vessels, hypertension, and smoking, HRs were 1.24 (95% CI 1.04-1.46) for fear of dying, 1.26 (95% CI 1.06-1.50) for helplessness, and 1.26 (95% CI 1.01-1.57) for pain.ConclusionsRetrospectively perceived MI-related distress in the form of fear of dying, helplessness, or pain was associated with non-fatal cardiovascular outcome independent of other important prognostic factors.

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Conceptualization, Measurement, and Analysis of Negative Affective Risk Factors

Cited by 14 publications

References 61 publications

Are we witnessing the decline effect in the Type D personality literature? What can be learned?

Are we witnessing the decline effect in the Type D personality literature? What can be learned?

Generalized anxiety disorder prevalence and comorbidity with depression in coronary heart disease: A meta-analysis

Distress related to myocardial infarction and cardiovascular outcome: a retrospective observational study

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