Psychosocial Factors Predicting Mastery in Type 2 Diabetes Mellitus - European Medical Journal
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Psychosocial Factors Predicting Mastery in Type 2 Diabetes Mellitus

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EMJ Cardiology 8.1 2020 Feature Image
Authors:
*Chantal F. Ski,1 Karen McGuigan,1 Alyson Hill,2 Vivien Coates,3,4 David R. Thompson,1 Maurice O’Kane,4 Deirdre McCay2
Disclosure:

The authors have declared no conflicts of interest.

Citation
EMJ Cardiol. ;8[1]:54-55. Abstract Review No: AR6.

Each article is made available under the terms of the Creative Commons Attribution-Non Commercial 4.0 License.

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BACKGROUND

Type 2 diabetes mellitus (T2D), like many other chronic conditions including cardiovascular disease, requires effective self-management to ensure optimal outcomes and reduce associated complications.1 Mastery is a recognised health protective factor among those with chronic conditions, with higher levels of mastery associated with better control of chronic conditions, treatment adherence, and improved health behaviours.2,3

The literature generally highlights the individual impact of psychosocial factors on effective self-management of chronic conditions. Depression is associated with poorer clinical outcomes, medication adherence, and motivation impacting negatively on self-management.4 Disempowerment is associated with poorer outcomes.5 Diabetes distress is negatively associated with self-management, glycaemic control, and adherence.5 However, little is known about how these psychosocial factors impact mastery.

METHODS

This study used baseline data drawn from a randomised controlled trial (RCT) of a structured diabetes education intervention. The sample comprised 131 participants with T2D aged 39–85 years (median: 62.3; standard deviation: 8.8), of whom 59.5% were male. Participants were assessed using: Problem Areas in Diabetes (PAID) scale, measuring diabetes related distress;6 Pearlin Mastery (PM) scale;7 Hospital Anxiety and Depression Scale (HADS);8 and the Diabetes Empowerment Scale-Short Form (DES-SF).9

The purpose of this study was to evaluate the moderating role of diabetes empowerment and depression in the relationship between diabetes distress and mastery. To test this, a moderated model was specified and tested in SPSS using PROCESS, a “logistic regression-based path analytical framework for estimating direct and indirect effects in simple and multiple moderation models.”10

RESULTS

All variables were statistically significant predictors of mastery. Diabetes distress (b: -0.249; t(5,112): -3.71; p<0.005) and depression (b: -0.980; t(5,112): -5.73; p<.005) were negatively associated with mastery; with diabetes empowerment (b: 0.280; t(5,112): 3.02; p<.005) positively associated. A significant interaction between diabetes-specific distress and depression was found, (b: 0.024; t(112): 3.79; p<.005), indicating that the magnitude of the diabetes distress effect on mastery depends on the level of depression. There was a significant increase in the variance in mastery explained because of the diabetes distress and depression interaction (F[1,112]: 14.40; p<.005; coefficient of determination [∆R2]: 0.06). A further increase in the mastery variance explained was found when the interaction was expanded to involve both moderators (F[2,112]: 16.88; p<.005; ∆R2: 0.14). The results highlight, at low levels of empowerment, increasing depression in the presence of increasing levels of distress predicted lower levels of mastery. This held true at both moderate and high levels of empowerment.

CONCLUSIONS

The significant interaction between diabetes distress and depression highlights how the negative impact of diabetes distress on mastery is heightened by increasing levels of depression, with this interaction creating greater reduction in mastery. Additionally, it appears that any positive effect of diabetes empowerment on mastery is eroded in the presence of diabetes distress and depression. The evidence suggests that the psychosocial interventions likely to have greatest impact on mastery are those that do not only focus on condition-specific distress, but also recognise and target key moderators, particularly depression.

References
Type 2 diabetes mellitus (T2D), like many other chronic conditions including cardiovascular disease, requires effective self-management to ensure optimal outcomes and reduce associated complications.1Wilkinson A et al. Factors influencing the ability to self-manage diabetes for adults liv-ing with Type 1 or 2 diabetes. Int J Nurs Stud. 2014;51:111-22. Roepke SK, Grant I. Toward a more complete understanding of the effects of personal mastery on cardiometabolic health. Health Psychol. 2011;30:615-32. O'Kearney EL et al. Mastery is associated with greater physical and mental health-related quality of life in two international cohorts of people with multiple sclerosis. Mult Scler Relat Disord. 2020;38:101481. Lee KP. Psychosocial factors associated with psychological insulin resistance in primary care patients in Hong Kong. J Clin Translat Endocrinol. 2015;2:157-62. Linetzky B et al. Exploring the role of the patient–physician relationship on insulin ad-herence and clinical outcomes in Type 2 diabetes: insights from the MOSAIc study. J Diabetes. 2017;9:596-605. Polonsky WH et al. Assessment of diabetes-related distress. Diabetes Care. 1995;18:754-60. Pearlin LI, Schooler I. The structure of coping. J Health Soc Behav. 1981;19:2-21. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67:361-70. Anderson RM et al. The Diabetes Empowerment Scale-Short Form (DES-SF). Diabetes Care. 2003;26:1641-2. Hayes AF. The PROCESS macro for SPSS and SAS. 2020. Available at: http://www.processmacro.org/index.html. Last accessed: 22 September 2020.