Parallel Mediation Model Linking Type D Personality with Adverse Health Outcomes in People with Type 2 Diabetes

doi:10.21203/rs.3.rs-910459/v1

Download PDF

Research

Parallel Mediation Model Linking Type D Personality with Adverse Health Outcomes in People with Type 2 Diabetes

https://doi.org/10.21203/rs.3.rs-910459/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 27 Dec, 2022

Read the published version in Nursing Open →

Version 1

posted

You are reading this older preprint version

Read the latest preprint version →

Background: This study aims to investigate a parallel mediation model to directly link Type D personality with adverse glycated hemoglobin (HbA1c) health outcomes and health-related quality of life (HRQOL), and indirectly through diabetes distress and social isolation in people with type 2 diabetes.

Methods: Secondary data analysis of a cross-sectional survey was used. Data on 524 people with type 2 diabetes from June 2020 to February 2021 were recruited from outpatient clinics. The analyzed components of the data set were Type D personality, diabetes distress, social isolation, HbA1c, and health-related quality of life (HRQOL). The hypothesized parallel mediation model was tested using the PROCESS macro for SPSS. A 10,000-bootstrap bias-corrected procedure was used to estimate 95% confidence intervals for indirect effects.

Results: Type D personality was present in 31.3% of the participants. The direct effect of Type D personality on HbA1c was insignificant, but was significant on HRQOL. The indirect effects of Type D personality on HbA1c and HRQOL through diabetes distress and social isolation were both significant. The indirect effect on HRQOL through diabetes distress was greater than that through social isolation.

Conclusion: People with a Type D personality more often experienced negative emotions in response to the burden of living with and managing diabetes and might have fewer interpersonal contacts, which in turn impair glycemic control and HRQOL. This study identified the mechanisms underlying the relationship between Type D personality and glycemic control and HRQOL in people with type 2 diabetes. Both diabetes distress and social isolation mediated these relationships. Health professionals must monitor people with type 2 diabetes to determine the presence of Type D personality. It is particularly recommended for those with Type D personality to be provided with interventions to reduce diabetes distress and to enhance social isolation in order to improve their glycemic control and HRQOL.

Health Economics & Outcomes Research

Health Policy

Diabetes

Distress

Social isolation

Glycemic control

Health-related quality of life

Type D personality

Type D (or “distressed”) personality is characterized by the combination of two stable personality traits: negative affectivity and social inhibition [1]. Negative affectivity denotes the tendency to experience negative emotions, and social inhibition denotes the tendency to inhibit self-expression during social interactions [2]. Although Type D personality originally emerged as a risk factor for adverse health outcomes in people with coronary health disease, it has since been recognized as also being a risk factor for people with other medical conditions [3]. However, there is insufficient evidence for this regarding people with type 2 diabetes [4].

According to the American Diabetes Association and European Association for the Study of Diabetes, the goals for treatment of type 2 diabetes are to control blood glucose in order to prevention or delay complications and to maintain the quality of life [5]. Glycated hemoglobin (HbA1c) is a standard objective marker of blood glucose control, reflecting average blood glucose levels over 2–3 months [6]. Despite the lack of a universally accepted definition, “quality of life” is too broad since it includes welfare, the economic situation, and health status, and instead “health-related quality of life” (HRQOL) is a more-concise outcome indicator for use in clinical situations [7]. From these perspectives, HbA1c and HRQOL can be representative outcome parameters for type 2 diabetes. Therefore, a negative association can be assumed between Type D personality and diabetes outcomes such as HbA1c and HRQOL.

Studies have been conducted on Type D personality in people with type 2 diabetes even in the early stage [8]. The few studies that examined the relationship between Type D personality and HbA1c in people with type 2 diabetes produced inconsistent findings. Some studies found that people with Type D personality were more likely to have higher HbA1c levels [4, 9, 10], while another study found no direct association and suggested exploring its indirect effect through mediators [11].

People with Type D personality with chronic disease, particularly with cardiovascular disease, have been reported to have greater impairment of HRQOL [12–14]. However, this relationship has rarely been investigated among people with diabetes. Conti et al. [9] were the first and only authors to empirically demonstrate this relationship in people with type 2 diabetes.

The mechanisms underlying the association between Type D personality and adverse clinical outcomes are unclear [15]. It is therefore necessary to determine which factors mediate the adverse effects of Type D personality on the outcomes [14]. Psychosocial factors have been conjectured as plausible mediators of this mechanism [16].

Diabetes distress regards negative emotions in response to the burden of living with and managing diabetes [17, 18]. A previous study of people with type 2 diabetes indicated that people with Type D personality had greater diabetes distress [19]. Greater diabetes distress was known to induce worse blood glycemic control [20, 21] and poor HRQOL in people with type 2 diabetes [22–24]. Together these observation studies suggest that the relationships between Type D personality and HbA1c and HRQOL would be mediated by diabetes distress.

Another plausible pathway for Type D personality predicting adverse diabetes outcomes is social isolation, characterized as a paucity of contact with others and a lack of social involvement [25]. Associations have been reported between Type D personality and social isolation in people with cardiovascular disease and those from a general population [26, 27]. Social isolation is known to be associated with HbA1c in people with diabetes [28], and negatively related to HRQOL among older adults [29, 30]. Accordingly, it may be postulated that Type D personality is associated with social isolation, which in turn relates to adverse HbA1c and HRQOL diabetes outcomes in people with type 2 diabetes.

A parallel mediation model is where two or more mediators linked by the same independent and outcome variables are not based on causality and are strongly correlated [31]. Since no evidence exists between the diabetes distress and social isolation mediators, these are expected to be parallel mediators in the association between Type D personality and the diabetes health outcomes of HbA1c and HRQOL.

Aim

This study aimed to investigate a parallel mediation model directly linking Type D personality with adverse health outcomes (HbA1c and HRQOL), and indirectly through both diabetes distress and social isolation in people with type 2 diabetes. The following two hypotheses were tested:

Hypothesis 1

Type D personality is directly related to HbA1c and indirectly related through both diabetes distress and social isolation in people with type 2 diabetes.

Hypothesis 2

Type D personality is directly related to HRQOL and indirectly related through both diabetes distress and social isolation in people with type 2 diabetes.

Study design and participants

This study performed a secondary analysis of data derived from a cross-sectional survey of people with type 2 diabetes [32]. Data were obtained on 524 people with type 2 diabetes from June 2020 to February 2021 who were recruited from outpatient clinics after the approval of the associated institutional review boards. The inclusion criteria for participants were being at least 19 years old, articulate in the Korean language, and undergoing a treatment regimen (oral hypoglycemic agents, insulin, or both) for type 2 diabetes. The mean age of participants was 60.35 years (SD = 11.19 years). About one-third were female (35.9%), and three-quarters (75.6%) were taking oral hypoglycemic agents. The mean duration of diagnosed diabetes was 11.77 years (SD = 8.72 years).

Measurement

Type D personality

Type D personality was identified using the 14-item Type D Scale (DS14), which consists of two 7-item subscales measuring negative affectivity (NA) and social inhibition (SI) [1]. Each item is scored on a 5-point rating scale ranging from 0 to 4, with subscale scores ranging from 0 to 28. The cutoff point for Type D personality categorization is a score of ≥ 10 on both the NA and SI subscales. In the original study, the Cronbach’s alpha values were .88 and .86 for NA and SI, respectively, and test–retest reliability coefficients were .72 and .82. The DS14 has been validated in various populations, including people with type 2 diabetes [19] and in Koreans [33]. In the present study, Cronbach’s alpha values for the NA and SI subscales were .86 and .78, respectively.

Diabetes distress

Diabetes distress was measured using a five-item short-form version of the Problem Areas in Diabetes (PAID-5) [34] scale derived from the original 20-item PAID [35]. Each item is scored on a 5-point Likert scale from “not a problem” to “a serious problem.” The possible total scores on the PAID-5 range from 0 to 20, with higher scores implying greater diabetes-related distress. The Korean version of the PAID-5 had satisfactory factorial structural validity, convergent validity, known-groups validity, internal consistency (Cronbach’s alpha = .87), and test–retest reliability (intraclass correlation coefficient: ICC = .89) among 440 people with type 2 diabetes [36]. In the present study, Cronbach’s alpha of the Korean version was .91.

Social isolation

Social isolation was measured using the five-item Social Isolation Index [25], which determines whether a respondent (1) is not married/not cohabiting with a partner; (2) does not participate in any organization, religious group, or committee; and has contact less frequently than monthly (including face-to-face, telephone, or written/e-mail) with (3) friends, (4) relatives, and (5) other family members they do not live with. The scores ranged from 0 to 5, with higher scores indicating greater social isolation.

Glycated hemoglobin

HbA1c, an integrated marker of glycemic control, was collected from the medical records of participants.

Health-related quality of life

The Diabetes-specific Quality of Life (D-QOL) was used to measure HRQOL and comprised 16 items, responses to which were provided on a 5-point Likert-type scale [37]. All items were reversed and averaged so that a higher score indicated a better HRQOL. The D-QOL demonstrated satisfactory content validity, factorial construct validity (using exploratory and confirmatory factor analyses), concurrent validity, known-groups validity, and internal consistency (Cronbach’s alpha = .92) among 402 people with diabetes. In the present study, Cronbach’s alpha of the D-QOL was .91.

Statistical analysis

Data were analyzed using SPSS (version 25.0 for Windows) and its PROCESS macro (version 3.5.3). Study variables were computed using descriptive statistics. Pearson’s correlation analysis, t-tests, and ANOVA were performed to identify any covariates between general participant characteristics and the mediator/outcome variables (diabetes distress, social isolation, HbA1c, and HRQOL). General characteristics associated with both mediators and outcome variables were considered covariates [31]. Statistical assumption tests were performed before the mediation analysis. Collinearity and multicollinearity among predicting variables were determined using point-biserial or Pearson’s correlation analysis, and the variance inflation factor (VIF). The Durbin-Watson statistic was computed to determine whether the residuals in the model were independent. Linearity and homoscedasticity assumptions were determined using a plot of standardized residuals against standardized predicted values [31, 38].

The hypothesized parallel mediation model was analyzed using the PROCESS macro [37]. A 10,000-bootstrap bias-corrected procedure was used to estimate the 95% confidence intervals (CIs) of the indirect effects. Data values were quoted to three decimal places. A significant indirect effect was indicated when the 95% CI of an indirect (mediation) effect did not span zero.

Preliminary analyses

Of the 524 participants, 31.3% (n = 164) were categorized as Type D personality. The mean values for diabetes distress, social isolation, HbA1c, and HRQOL were 8.38 (SD = 5.29), 1.07 (SD = 1.03), 7.30 (SD = 1.27), and 2.96 (SD = 0.75), respectively.

There were no covariates among the general characteristics that were associated with both mediators and the HbA1c outcome variable. However, gender was significantly associated with diabetes distress and HRQOL, and education level was associated with social isolation and HRQOL (Additional file 1: Table S1). Gender and education level were therefore included as covariates in the subsequent parallel mediation model linking Type D personality and HRQOL.

Type D personality demonstrated a positive correlation with diabetes distress (r_pb = .29, p \(cript>\) .001) and social isolation (r_pb = .18, p \(cript>\) .001). Diabetes distress had a weak correlation with social isolation (r = .10, p \(cript>\) .015). The VIF values for all predicting variables were < 10 for the HbA1c (1.04–1.12) and HRQOL (1.04–1.12) diabetes health outcomes, indication no problem of high redundancy among predicting variables. Dubin-Watson values were near 2 (1.92 and 1.90 for HbA1c and HRQOL, respectively) for the independent residuals of the dependent variables (no autocorrelation). The standardized residual plot against standardized predicted values for HbA1c and HRQOL indicated satisfactory linearity (the Loess curve centers along the entire X axis were close to zero) and homoscedasticity (data were consistently and equally spread on the Y axis throughout the plot).

Hypothesis 1

Figure 1 (and Additional file 1: Table S2) indicate that Type D personality significantly predicted both diabetes distress (a₁ = 3.314, p < .001) and social isolation (a₂ = 0.397, p < .001). HbA1c exhibited significant regression with diabetes distress (b₁ = 0.026, p = .021) and social isolation (b₂ = 0.136, p = .013) when holding other variables constant. However, the direct effect (c’ = 0.062, p = .622) of Type D personality on HbA1c was insignificant after controlling for diabetes distress and social isolation.

Table 1 indicates that the indirect effect (a₁ × b₁ = 3.314 × 0.026 = 0.083) of Type D personality on HbA1c via diabetes distress after controlling for social isolation was significant, because the 95% bootstrap CI (0.014–0.163) did not include zero. This suggest that participants with Type D personality scored 0.083 points higher than those without Type D personality on HbA1c due to the indirect effect through diabetes distress, when holding social isolation constant. The indirect effect (a₂ × b₂ = 0.397 × 0.136 = 0.054) of Type D personality on HbA1c through social isolation was also significant after controlling for diabetes distress (95% bootstrap CI = 0.007 to 0.121). Comparing the magnitudes of the two indirect effects revealed an insignificant difference (95% bootstrap CI = − 0.061 to 0.121); however, the total effect was insignificant (c = 0.199, p = .096).

Table 1

Indirect effects on HbA1c with 95% bootstrap confidence interval
	Product of coefficient		95% bootstrap CI
	Point estimate	Bootstrap SE	Lower limit	Upper limit
Indirect effects on HbA1c
a₁ × b₁	0.083	0.038	0.014	0.163
a₂ × b₂	0.054	0.029	0.007	0.121
Comparison between indirect effects on HbA1c (a₁ × b₁ minus a₂ × b₂)	0.029	0.046	–0.061	0.121
CI: confidence interval; SE: standard error. a₁ × b₁: indirect effect of Type D personality on HbA1c through diabetes distress; a₂ × b₂: indirect effect of Type D personality on HbA1c through social isolation.

Hypothesis 2

Figure 2 (and Additional file 1: Table S3) 3 indicate that all regression coefficients were significant, including the direct effect (c’ = − 0.326, p < .001) of Type D personality on HRQOL after controlling for mediators and covariates. Table 2 indicates that the indirect effect (a₁ × b₁ = − 0.254) of Type D personality on HRQOL through diabetes distress was significant after controlling for social isolation and covariates (95% bootstrap CI = − 0.335 to − 0.178). The indirect effect (a₂ × b₂ = − 0.029) through social isolation was also significant after controlling for diabetes distress and covariates (95% bootstrap CI = − 0.056 to − 0.008). The indirect effect through diabetes distress was greater than through social isolation (95% bootstrap CI = − 0.316 to − 0.145). The total effect was significant (c = − 0.609, p < .001).

Table 2

Indirect effects on HRQOL with 95% bootstrap confidence interval while controlling for covariates
	Product of coefficient		95% bootstrap CI
	Point estimate	Bootstrap SE	Lower limit	Upper limit
Indirect effects on HRQOL
a₁ × b₁	–0.245	0.040	–0.335	–0.178
a₂ × b₂	–0.029	0.012	–0.056	–0.008
Comparison between indirect effects on HRQOL (a₁ × b₁ minus a₂ × b₂)	–0.226	0.042	–0.312	–0.145
CI: confidence interval; SE: standard error. a₁ × b₁: indirect effect of Type D personality on HRQOL through diabetes distress; a₂ × b₂: indirect effect of Type D personality on HRQOL through social isolation.

In this study, 31.3% of the participants with type 2 diabetes had a Type D personality. This rate was consistent with the ranges reported previously among Dutch (22.8–55.8%) [11, 39] and Chinese (27.9–41.4%) [10, 40] adults with type 2 diabetes.

In this study, the mean HbA1c level of people with Type D personality was the same as that of people without Type D personality. Nefs et al. [11] similarly reported no difference after subdividing people without Type D personality into three groups based on scores higher or lower than the cutoff of 10 for the NA and SI sum scores (NA⁺SI⁻, NA⁻SI⁺, and NA⁻SI⁻). In contrast, another study that analyzed the continuous scores of the NA and SI sums found a significant relationship between Type D personality (NA) and HbA1c [9]. Li et al. [41] suggested that the association between Type D personality and HbA1c might differ with the analysis method, including whether Type D was operationalized as a categorical or continuous variable.

Type D personality has mostly been included as a categorical variable (e.g., Type D vs. not Type D) using a cutoff point of 10, while the personality was included as a continuous variable using scores from 0 to 28 for both the NA and SI constructs. Regarding the categorical approach, the cutoff point of 10 was criticized based on the value of the median split [42]. However, the cutoff point of 10 was demonstrated as accurate in classifying Type D vs. not Type D using item response theory analysis among people with cardiovascular diseases [43]. Those against the categorical approach insisted that Type D personality was more accurately represented by the continuous constructs of NA and SI [42] or was analyzed more effectively using a continuous interaction method including quadratic NA and SI effects [44]. This controversy means that further exploration is needed into how to deal with the Type D personality variable.

In this study, those with Type D personality had poor HRQOL. This finding was consistent with that of the sole study conducted on people with type 2 diabetes [9]. That previous study measured HRQOL using a generic instrument (the World Health Organization QOL-BREF: WHOQOL-BREF) that measured physical health, psychological variables (e.g., self-esteem), social relationships (e.g., social support), and environment (e.g., physical safety) [45]. The generic type is applicable when measuring HRQOL across healthy and disease populations [7]. In clinical situations, using a disease-specific type of HRQOL instrument designed to focus on specific problems induced by an illness and its treatment, such as diabetes, is more effective [37]. We recommend conducting more studies on the relationship between Type D personality and HRQOL, with a particular focus on using a diabetes-specific HRQOL instrument.

The present study was the first that we know of to test the association between Type D personality and diabetes outcomes (HbA1c and HRQOL) through multiple mediators among people with type 2 diabetes. In this study, the two hypotheses for the indirect effects through both diabetes distress and social isolation were supported. This mediation-based research provided new information on how people with Type D personality easily experience negative emotions in response to the burden of living with and managing diabetes, and might have fewer interpersonal contacts with others (e.g., with family, friends, or health professionals) and be more socially withdrawn, which will negatively impact blood glycemic control and HRQOL. This new information may contribute to furthering comprehensive theory development regarding Type D personality and its effects on people with type 2 diabetes.

Implications for practice

In this study, the findings for the indirect effects suggest directions for furthering practice for people with type 2 diabetes. First, we recommend that health professionals monitor clients with type 2 diabetes to determine the presence of Type D personality, which is a risk factor for adverse blood glycemic control and HRQOL. The health professionals must then plan and provide interventions toward reducing diabetes distress and social isolation, particularly for those with Type D personality. For example, we suggest that applying diabetes-specific psychological interventions had supporting evidence from a meta-analysis of randomized controlled trial studies toward reducing diabetes distress [46]. Others have indicated that using active listening and talking about the emotional experiences of patient also exert similar effects on reducing diabetes distress when compared with a psychological intervention [47]. Chen and Schulz [48] asserted that social interventions based around information and communications technology (ICT) such as using the internet or web-based apps would promote social contact and alleviate social isolation by providing connections with the outside world, improving social support, increasing engagement with activities of interest, and boosting self-confidence. ICT interventions using digital devices may be particularly useful during the current coronavirus disease-19 pandemic, which requires non-face-to-face contact, social distancing, and restricted gatherings [49].

Strengths and limitation

The first strength of this study was the use of a bootstrapping method for the statistical mediation analysis. The traditional method for a mediation test by Baron and Kenney [50] has previously being the most common. However, this method has been criticized for its lack of statistical power and its failure in testing indirect effects, and no longer seems to be recommended [31, 51]. The normal theory approach, called the Sobel test, has been used as a type of mediation analysis, but is criticized due to its inability to cope with indirect effects that have an asymmetric distribution [51]. To overcome the normality assumption, it is recommended to use the bootstrapping method, which provides more power in detecting indirect effects and reduces the risk of type I errors [52]. Structural equation modeling (SEM) is also frequently used for mediation analysis, and has the advantage of accounting for random measurement errors; however, results from a sufficient sample are substantially identical when applying the SEM and PROCESS-bootstrapping methods [53]. The second strength of the present study was the consideration of potential covariates among general participant characteristics, which might have threatened with the findings of the mediation model.

The main limitation of this study was its cross-sectional design, which induced difficult temporal interpretations of the mediation effects between Type D personality and adverse diabetes outcomes. Further research is recommended to use a longitudinal design.

Type D personality was found to directly affect HRQOL but not HbA1c among people with type 2 diabetes. Type D personality indirectly affected HbA1c and HRQOL through the diabetes distress and social isolation mediators, respectively. The indirect effect of Type D personality on HRQOL through diabetes distress was greater than through social isolation. For people with Type D personality, we recommend providing interventions to reduce diabetes distress and enhance social isolation, which in turn will improve their HbA1c and HRQOL.

Type D personality

distressed personality

HbA1c

Glycated hemoglobin

HRQOL

health-related quality of life

DS14

Type D scale

negative affectivity

social inhibition

PAID

Problem Areas in Diabetes

ICC

intraclass correlation coefficient

D-QOL

Diabetes-specific Quality of Life

VIF

variance inflation factor

CIs

confidence intervals

ICT

information and communication

SEM

structural equation modeling

Funding This research was supported by a grant from the National Research Foundation of Korea (NRF) funded by the government of the Republic of Korea (MSIT) (NRF-2018R1A2B6001719). The funder did not participate in conducting or publishing the study.

Conflict of interest The authors have no conflict of interest to declare.

Ethical approval Ethical approval was obtained from the institutional review boards of the included university hospitals in South Korea (AJIRB-SBR-SUR-18-535; IUH-IRB 2020-05-036; CNUH-2020-176).

Informed consent Written informed consent was obtained from all participants included in this study.

Author contributions E.-H.L: study conception and design; funding acquisition; data analysis and interpretation; draft preparation, review, and editing of the manuscript; approval of the submitted version of the manuscript. Y.H.L., D.C., E.H.K., and H.-J.K.: investigation; data interpretation; review and editing of the manuscript; approval of the submitted version of the manuscript.

Denollet J. DS14: standard assessment of negative affectivity, social inhibition, and type D personality. Psychosom Med. 2005;67:89–97. https://doi.org/10.1097/01.psy.0000149256.81953.49.
Denollet J. Type D personality: a potential risk factor refined. J Psychosom Res. 2000;49:255–66. https://doi.org/10.1016/s0022-3999(00)00177-x.
Mols F, Denollet J. Type D personality among noncardiovascular patient populations: a systematic review. Gen Hos Psychiatry. 2010;32:66–72. https://doi.org/10.1016/j.genhosppsych.2009.09.010.
Shao Y, Yin H, Wan C. Type D personality as a predictor of self-efficacy and social support in patients with type 2 diabetes mellitus. Neuropsychiatr Dis Treat. 2017;13:855–61. https://doi.org/10.2147/ndt.s128432.
Davies MJ, D’Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, Rossing P, Tsapas A, Wexler DJ, Buse JB. Management of hyperglycemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018;41:2669–701. https://doi.org/10.2337/dci18-0033.
The International Expert Committee. International expert committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 2009;32:1327–34. https://doi.org/10.2337/dc09-9033.
Fayers PM, Machin D. Quality of life: The assessment, analysis and interpretation of patient-reported outcomes. 6th ed.: John Wiley & Sons; 2007.
Conti C, Carrozzino D, Patierno C, Vitacolonna E, Fulcheri M. The clinical link between type D personality and diabetes. Front Psychol. 2016;7:113. https://doi.org/10.3389/fpsyt.2016.00113.
Conti C, Di Francesco G, Fontanella L, Carrozzino D, Patierno C, Vitacolonna E, Fulcheri M. Negative affectivity predicts lower quality of life and metabolic control in type 2 diabetes patients: A structural equation modeling approach. Front Psychol. 2017;8:831. https://doi.org/10.3389/fpsyg.2017.00831.
Lin YH, Chen DA, Lin C, Huang H. Type D personalityï»¿ is associated with glycemic control and socio-psychological factors on patients with type 2 diabetes mellitus: A cross-sectional study. Psychol Res Behav Manag. 2020;13:373–81. https://doi.org/10.2147/prbm.s245226.
Nefs G, Speight J, Pouwer F, Pop V, Bot M, Denollet J. Type D personality, suboptimal health behaviors and emotional distress in adults with diabetes: Results from diabetes miles–the Netherlands. Diabetes Res Clin Pract. 2015;108:94–105. https://doi.org/10.1016/j.diabres.2015.01.015.
Aquarius AE, Denollet J, de Vries J, Hamming JF. Poor health-related quality of life in patients with peripheral arterial disease: Type D personality and severity of peripheral arterial disease as independent predictors. J Vasc Surg. 2007;46:507–12. https://doi.org/10.1016/j.jvs.2007.04.039.
Jo E, Kim SR, Kim HY. Predictive model for quality of life in patients with recurrent coronary artery disease. Euro J Cardiovasc Nurs. 2019;18:501–11. https://doi.org/10.1177/1474515119847544.
Staniute M, Brozaitiene J, Burkauskas J, Kazukauskiene N, Mickuviene N, Bunevicius R. Type D. personality, mental distress, social support and health-related quality of life in coronary artery disease patients with heart failure: a longitudinal observational study. Health Qual Life Outcomes. 2015;13:1–11. https://doi.org/10.1186/s12955-014-0204-2.
Huang I-C, Lee JY, Ketheeswaran P, Jones CM, Revicki DA, Wu AW. Does personality affect health-related quality of life? a systematic review. PLoS ONE. 2017;12:e0173806. https://doi.org/10.1371/journal.pone.0173806.
Williams L, O'Connor RC, Howard S, Hughes BM, Johnston DW, Hay JL, O’Connor DB, Lewis CA, Furguson E, Sheehy N, Grealy MA, O’Carroll RE. Type-D personality mechanisms of effect: the role of health-related behavior and social support. J Psychosomatic Res. 2008;64:63–9. https://doi.org/10.1016/j.jpsychores.2007.06.008.
Fisher L, Hessler DM, Polonsky WH, Mullan J. When is diabetes distress clinically meaningful?: Establishing cut points for the diabetes distress scale. Diabetes Care. 2012;35:259–64. https://doi.org/10.2337/dc11-1572.
Gonzalez JS, Fisher L, Polonsky WH. Depression in diabetes: have we been missing something important? Diabetes Care. 2011;34:236–9. https://doi.org/10.2337/dc10-1970.
Nefs G, Pouwer F, Pop V, Denollet J. Type D (distressed) personality in primary care patients with type 2 diabetes: validation and clinical correlates of the DS14 assessment. J Psychosomatic Res. 2012;72:251–7. https://doi.org/10.1016/j.jpsychores.2012.01.006.
Asuzu CC, Walker RJ, Williams JS, Egede LE. Pathways for the relationship between diabetes distress, depression, fatalism and glycemic control in adults with type 2 diabetes. J Diabetes Complicat. 2017;31:169–74. https://doi.org/10.1016/j.jdiacomp.2016.09.013.
Fisher L, Glasgow RE, Strycker LA. The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes. Diabetes Care. 2010;33:1034–6. https://doi.org/10.2337/dc09-2175.
Carper MM, TraegerL, Gonzalez JS, Wexler DJ, Psaros C, Safren SA. The differential associations of depression and diabetes distress with quality of life domains in type 2 diabetes. J Behav Med. 2014;37:501–10. https://doi.org/10.1007/s10865-013-9505-x.
Jannoo Z, Wah YB, Lazim AM, Hassali MA. Examining diabetes distress, medication adherence, diabetes self-care activities, diabetes-specific quality of life and health-related quality of life among type 2 diabetes mellitus patients. J Clin Transl Endocrinol. 2017;9:48–54. https://doi.org/10.1016/j.jcte.2017.07.003.
Wang RH, Lin CC, Chen SY, Hsu HC, Huang CL. The impact of self-stigma, role strain, and diabetes distress on quality of life and glycemic control in women with diabetes: a 6-month prospective study. Biol Res Nurs. 2021. doi.org/10.1177/10998004211009606.
Shankar A, McMunn A, Banks J, Steptoe A. Loneliness, social isolation, and behavioral and biological health indicators in older adults. Health Psychol. 2011;30:377–85. https://doi.org/10.1037/a0022826.
Michal M, Wiltink J, Grande G, Beute ME, Brähler E. Type D personality is independently associated with major psychosocial stressors and increased health care utilization in the general population. J Affect Disord. 2011;134:396–403. https://doi.org/10.1016/j.jad.2011.05.033.
Rashidi M, Ahmadian H, Tabaqian N, Amadi Tahour Soltani M. Correlation of attachment styles and early maladaptive schemas with Type D personality in cardiovascular patients. J Police Med. 2017;6:85–92. https://doi.org/10.30505/6.2.85.
Ida S, Kaneko R, Imataka K, Okubo K, Shirakura Y, Azuma K, Fujiwara R, Takahashi H, Murata K. Factors associated with social isolation and being homebound among older patients with diabetes: a cross-sectional study. BMJ open. 2020;10:e037528. https://doi.org/10.1136/bmjopen-2020-037528.
Beridze G, Ayala A, Ribeiro O, Fernández-Mayoralas G, Rodríguez-Blázquez C, Rodríguez-Rodríguez V, Rozo-Pérezo F, Joáo-Forjaz M, Calderón-Larrañaga A. Are loneliness and social isolation associated with quality of life in older adults? Insights from Northern and Southern Europe. Int J Environ Res Public Health. 2020;17:8637. https://doi.org/10.3390/ijerph17228637.
Hawton A, Green C, Dicken AP, Richards SH, Taylor RS, Edwards R, Greaves CJ, Campbell JL. The impact of social isolation on the health status and health-related quality of life of older people. Qual Life Res. 2011;20:57–67. https://doi.org/10.1007/s11136-010-9717-2.
Lee EH, Lee KW, Hong S, Kim SH, Chung JO. Serial mediation model to link health literacy with self-management in people with type 2 diabetes. J Adv Nurs. 2021(in process).
Lim HE, Lee MS, Ko YH, Park YM, Joe SH, Kim YK, Han C, Lee H-Y, Pedersen SS, Denollet J. Assessment of the type D personality construct in the Korean population: a validation study of the Korean DS14. J Korean Med Sci. 2011;26:116–23. https://doi.org/10.3346/jkms.2011.26.1.116.
McGuire B, Morrison T, Hermanns N, Skovlund S, Eldrup E, Gagliardino J, Kokoszka A. Matthews D. Pibernik-Okanovic M, Rodríguez-Saldaña J, de Wit M, Rodríguez-Saldaña J. Short-form measures of diabetes-related emotional distress: the problem areas in diabetes scale (PAID)-5 and PAID-1. Diabetologia. 2010;53:66–9. https://doi.org/10.1007/s00125-009-1559-5.
Polonsky WH, Anderson BJ, Lohrer PA, Welch G, Jacobson AM, Aponte JE, Schwartz CE. Assessment of diabetes-related distress. Diabetes Care. 1995;18:754–60. https://doi.org/10.2337/diacare.18.6.754.
Lee EH, Lee YW, Lee KW, Kim YS, Nam MS. Measurement of diabetes-related emotional distress using the Problem Areas in Diabetes scale: psychometric evaluations show that the short form is better than the full form. Health Qual Life Outcomes. 2014;12:1–9. https://doi.org/10.1186/s12955-014-0142-z.
Lee E-H, Lee YW, Lee K-W, Kim DJ, Kim S-K. Development and psychometric evaluation of a diabetes-specific quality of life (D-QOL) scale. Diabetes Res Clin Pract. 2012;95:76–84. https://doi.org/10.1016/j.diabres.2011.08.022.
Hayes AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford publications; 2013.
Tabachnick B, Fidell L. Using multivariate statistics. 6th ed.: Pearson Education Inc; 2013.
van Dooren FE, Denollet J, Verhey FR, Stehouwer CD, Sep SJS, Henry RMA, Kremers SPJ, Dagnelie PC, Schaper NC, van der Kallen CJ. Psychological and personality factors in type 2 diabetes mellitus, presenting the rationale and exploratory results from the Maastricht study, a population-based cohort study. BMC Psychiatry. 2016;16:17. https://doi.org/10.1186/s12888-016-0722-z.
Li X, Zhang S, Xu H, Tang X, Zhou H, Yuan J, Wang X, Qu Z, Wang F, Zhu H. Guo S, Tian D, Zhang W. Type D personality predicts poor medication adherence in Chinese patients with type 2 diabetes mellitus: a six-month follow-up study. PloS one. 2016;11:e0146892. https://doi.org/10.1371/journal.pone.0146892.
Li X, Gao M, Zhang S, Xu H, Zhou H, Wang X, Qu Z, Guo Z, Zhang W, Tian D. Medication adherence mediates the association between type D personality and high HbA1c level in Chinese patients with type 2 diabetes mellitus: a six-month follow-up study. J Diabetes Res. 2017;7589184. https://doi.org/10.1155/2017/7589184.
Ferguson E, Williams L, O’Connor RC, Howard S, Hughes BM, Johnston DW, Allan JA, O’Conner DB, Lewis CL, Grealy MA, O’Carroll RE. A taxometric analysis of type-D personality. Psychosom Med. 2009;71:981–6. https://doi.org/10.1097/psy.0b013e3181bd888b.
Emons WH, Meijer RR, Denolle J. Negative affectivity and social inhibition in cardiovascular disease: Evaluating type-D personality and its assessment using item response theory. J Psychosom Res. 2007;63:27–39. https://doi.org/10.1016/j.jpsychores.2007.03.010.
Lodder P. A re-evaluation of the type D personality effect. Pers Individ Differ. 2020;167:110254. https://doi.org/10.1016/j.paid.2020.110254.
The WHOQOL Group. Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol Med. 1998;28:551–8. https://doi.org/10.1017/s0033291798006667.
Schmidt C, van Loon BP, Vergouwen A, Snoek F, Honig A. Systematic review and meta-analysis of psychological interventions in people with diabetes and elevated diabetes‐distress. Diabetic Med. 2018;35:1157–72. https://doi.org/10.1111/dme.13709.
Chew B, Vos R, Stellato R, Ismail M, Rutten G. The effectiveness of an emotion-focused educational programme in reducing diabetes distress in adults with type 2 diabetes mellitus (VEMOFIT): a cluster randomized controlled trial. Diabetic Med. 2018;35:750–9. https://doi.org/10.1111/dme.13615.
Chen YRR, Schulz PJ. The effect of information communication technology interventions on reducing social isolation in the elderly: a systematic review. J Med Internet Res. 2016;18:e18. https://doi.org/10.2196/jmir.4596.
Chatterjee P, Yatnatti SK. Intergenerational digital engagement: a way to prevent social isolation during the COVID-19 crisis. J Am Geriatr Soc. 2020;68:1394–5. https://doi.org/10.1111/jgs.16563.
Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research. conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51:1173–82. https://doi.org/10.1037/0022-3514.51.6.1173.
MacKinnon DP, Lockwood CM, Hoffman JM, West SG, Sheets V. A comparison of methods to test mediation and other intervening variable effects. Psychol Methods. 2002;7:83–104. https://doi.org/10.1037/1082-989X.7.1.83.
Hayes AF. Scharkow M. The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Sci. 2013;24:1918–27. https://doi.org/10.1177/0956797613480187.
Hayes AF, Montoya AK, Rockwood NJ. The analysis of mechanisms and their contingencies: PROCESS versus structural equation modeling. Australas Mark J. 2017;25:76–81. https://doi.org/10.1016/j.ausmj.2017.02.001.

SupplementaryTables20210914.docx

Download PDF

Journal Publication

published 27 Dec, 2022

Read the published version in Nursing Open →

Version 1

posted

You are reading this older preprint version

Read the latest preprint version →

Parallel Mediation Model Linking Type D Personality with Adverse Health Outcomes in People with Type 2 Diabetes

Status:

Journal Publication

Version 1

Abstract

Figures

Background

Methods

Aim

Study design and participants

Measurement

Type D personality

Diabetes distress

Social isolation

Glycated hemoglobin

Health-related quality of life

Statistical analysis

Results

Preliminary analyses

Hypothesis 1

Hypothesis 2

Discussion

Implications for practice

Strengths and limitation

Conclusions

List Of Abbreviations

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1