A systematic review comparing two popular methods to assess a Type D personality effect

Introduction:  Type D personality, operationalized as high scores on negative affectivity (NA) and social inhibition (SI), has been associated with various medical and psychosocial outcomes. The recent failure to replicate several earlier findings could result from the various methods used to assess the Type D effect. Despite recommendations to analyze the continuous NA and SI scores, a popular approach groups people as having Type D personality or not. This method does not adequately detect a Type D effect as it is also sensitive to main effects of NA or SI only, suggesting the literature contains false positive Type D effects. Here, we systematically assess the extent of this problem. Method:  We conducted a systematic review including 44 published studies assessing a Type D effect with both a continuous and dichotomous operationalization. Results:  The dichotomous method showed poor agreement with the continuous Type D effect. Of the 89 significant dichotomous method effects, 37 (41.6%) were Type D effects according to the continuous method. The remaining 52 (58.4%) are therefore likely not Type D effects based on the continuous method, as 42 (47.2%) were main effects of NA or SI only. Conclusion:  Half of the published Type D effect according to the dichotomous method may be false positives, with only NA or SI driving the outcome

Evaluating the psychometric properties of the Swedish version of the Impostor Profile scale (IPP30)

The Impostor Profile scale (IPP30) is a recently developed tool designed to delve into the nuanced aspects of the Impostor Phenomenon (IP), a psychological phenomenon where individuals wrongly attribute their successes to external factors, discounting their own abilities and often feeling like frauds. This study aimed to assess the psychometric properties, including factor structure, internal consistency, and nomological validity, of the Swedish version of IPP30 (S-IPP30). In a sample of Swedish students (N = 1,010; 76.7% women; Mage = 25.65, SDage = 6.43), Exploratory and Confirmatory Factor Analyses were conducted to scrutinize S-IPP30’s structure. The analyses supported a bifactor model with six specific factors and one overarching factor. However, two items in the scale displayed poor alignment with their intended subscales, adversely affecting the internal consistency of the two subscales. Consequently, a rephrasing of these items was suggested. The remaining four S-IPP30 subscales exhibited good internal consistency (Cronbach’s α = 0.76–0.90, McDonald’s ω = 0.77–0.91). Convergent validity was confirmed by largely replicating correlations among various S-IPP30 facets, the unidimensional IP measure, personality variables, and self-esteem, thereby accomplishing the goal of validating S-IPP30. This proposed modification of the two items requires further validation using a new sample to ensure its appropriateness and effectiveness in measuring the intended constructs

A systematic review comparing two popular methods to assess a Type D personality effect

Introduction:  Type D personality, operationalized as high scores on negative affectivity (NA) and social inhibition (SI), has been associated with various medical and psychosocial outcomes. The recent failure to replicate several earlier findings could result from the various methods used to assess the Type D effect. Despite recommendations to analyze the continuous NA and SI scores, a popular approach groups people as having Type D personality or not. This method does not adequately detect a Type D effect as it is also sensitive to main effects of NA or SI only, suggesting the literature contains false positive Type D effects. Here, we systematically assess the extent of this problem. Method:  We conducted a systematic review including 44 published studies assessing a Type D effect with both a continuous and dichotomous operationalization. Results:  The dichotomous method showed poor agreement with the continuous Type D effect. Of the 89 significant dichotomous method effects, 37 (41.6%) were Type D effects according to the continuous method. The remaining 52 (58.4%) are therefore likely not Type D effects based on the continuous method, as 42 (47.2%) were main effects of NA or SI only. Conclusion:  Half of the published Type D effect according to the dichotomous method may be false positives, with only NA or SI driving the outcome

Type D Personality as a Risk Factor for Adverse Outcome in Patients With Cardiovascular Disease: An Individual Patient-Data Meta-analysis

Objective Type D personality, a joint tendency toward negative affectivity and social inhibition, has been linked to adverse events in patients with heart disease, although with inconsistent findings. Here, we apply an individual patient-data meta-analysis to data from 19 prospective cohort studies (N = 11,151) to investigate the prediction of adverse outcomes by type D personality in patients with acquired cardiovascular disease. Method For each outcome (all-cause mortality, cardiac mortality, myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, major adverse cardiac event, any adverse event), we estimated type D's prognostic influence and the moderation by age, sex, and disease type. Results In patients with cardiovascular disease, evidence for a type D effect in terms of the Bayes factor (BF) was strong for major adverse cardiac event (BF = 42.5; odds ratio [OR] = 1.14) and any adverse event (BF = 129.4; OR = 1.15). Evidence for the null hypothesis was found for all-cause mortality (BF = 45.9; OR = 1.03), cardiac mortality (BF = 23.7; OR = 0.99), and myocardial infarction (BF = 16.9; OR = 1.12), suggesting that type D had no effect on these outcomes. This evidence was similar in the subset of patients with coronary artery disease (CAD), but inconclusive for patients with heart failure (HF). Positive effects were found for negative affectivity on cardiac and all-cause mortality, with the latter being more pronounced in male than female patients. Conclusion Across 19 prospective cohort studies, type D predicts adverse events in patients with CAD, whereas evidence in patients with HF was inconclusive. In both patients with CAD and HF, we found evidence for a null effect of type D on cardiac and all-cause mortality

Type D personality as a risk factor for adverse outcome in patients with cardiovascular disease: An individual patient data meta-analysis

Objective:  Type D personality, a joint tendency toward negative affectivity (NA) and social inhibition (SI), has been linked to adverse events in patients with heart disease, though with inconsistent findings. Here, we apply an individual patient-data meta-analysis to data from 19 prospective cohort studies (N = 11151), to investigate the prediction of adverse outcomes by Type D personality in acquired cardiovascular disease (CVD) patients. Method:  For each outcome (all-cause mortality, cardiac mortality, myocardial infarction (MI), coronary artery bypass grafting, percutaneous coronary intervention, major adverse cardiac event (MACE), any adverse event), we estimated Type D's prognostic influence and the moderation by age, sex, and disease type. Results:  In CVD patients, evidence for a Type D effect in terms of the Bayes factor (BF) was strong for MACE (BF = 42.5; OR = 1.14) and any adverse event (BF = 129.4; OR = 1.15). Evidence for the null hypothesis was found for all-cause mortality (BF = 45.9; OR = 1.03), cardiac mortality (BF = 23.7; OR = 0.99) and MI (BF = 16.9; OR = 1.12), suggesting Type D had no effect on these outcomes. This evidence was similar in the subset of coronary artery disease (CAD) patients, but inconclusive for heart failure (HF) patients. Positive effects were found for NA on cardiac- and all-cause mortality, the latter being more pronounced in males than females. Conclusion:  Across 19 prospective cohort studies, Type D predicts adverse events in CAD patients, while evidence in HF patients was inconclusive. In both CAD and HF patients, we found evidence for a null effect of Type D on cardiac- and all-cause mortality