Personality Correlates of Adherence to Type 2 Diabetes Regimens

Hyphantis, Thomas; Καλτσούδα, Άννα; Triantafillidis, John K.; Platis, Odysseas; Karadagi, Soula; Mantas, Christos; Argyropoulos, Argyrios; Mavreas, Venetsanos

doi:10.2190/nbqa-08a7-6mg9-gc8w

Cited by 25 publications

(29 citation statements)

References 7 publications

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Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

“…In previous studies, FFM personality factors have been associated with other important health behaviors and outcomes. [20][21][22][23][24][25][26][27][28][29][30][31] Thus, personality effects could have important consequences for the validity and applicability of RCT fi ndings.…”

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

“…Similarly, individuals with higher levels of Agreeableness tend to be more compliant and eager to please, 17,34 characteristics rendering RCT completion more likely. Finally, higher levels of Conscientiousness have been associated with greater dutifulness 34 and treatment adherence, [25][26][27][28][29][30][31] characteristics likely to reduce RCT attrition. These fi ndings suggest a discrete psychological profi le predicting missing trial data may exist.…”

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

“…In light of the well-established association between Conscientiousness and treatment adherence, [25][26][27][28][29][30][31] such approaches might also be considered for improving treatment adherence in clinical practice.…”

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

“…[20][21][22][23][24] Higher levels of Conscientiousness have been consistently associated with better adherence to chronic illness therapies. [25][26][27][28][29][30][31] Similar associations might exist between Conscientiousness and incomplete trial data, but no studies have addressed this question, and associations between other FFM factors and missing data are also unexplored.We examined the relationship of FFM personality factors to missing data in a RCT of Homing in on Health (HIOH), which was developed to make the Chronic Disease Self-Management Program (CDSMP) 32,33 available to persons less able or willing to participate in group training. The goals were to determine whether in-home and telephone-delivered HIOH would enhance self-effi cacy, or confi dence for executing self-management tasks, and improve outcomes in persons with chronic conditions.…”

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confidence: 99%

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Is Personality a Key Predictor of Missing Study Data? An Analysis From a Randomized Controlled Trial

Jerant¹,

Chapman²,

Duberstein³

et al. 2009

The Annals of Family Medicine

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PURPOSE Little is known regarding the effects of psychological factors on data collection in research studies. We examined whether Five Factor Model (FFM) personality factors-Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness-predicted missing data in a randomized controlled trial (RCT).METHODS Individuals (N = 415) aged 40 years and older with various chronic conditions, plus basic activity impairment, depressive symptoms, or both, were recruited from a primary care network and enrolled in a 6-week RCT of an illness self-management intervention, delivered by means of home visits or telephone calls or usual care. Random effects logistic regression modeling was used to examine whether FFM factors predicted missing illness management self-effi cacy data at any scheduled follow-up (2, 4, and 6 weeks, and 6 and 12 months), controlling for disease burden, study arm, and sociodemographic characteristics.RESULTS Across all follow-up points, the missing data rate was 4.5%. Higher levels of Openness (adjusted odds ratio [AOR] for 1-SD increase = 0.24; 95% CI, 0.12-0.46; P <.001), Agreeableness (AOR = 0.29; CI 0.14-0.60; P = .001), and Conscientiousness (AOR = 0.24; CI 0.15-0.50; P <.001) were independently associated with fewer missing data. Accuracy of the missing data prediction model increased when personality variables were added (change in area under the receiver operating characteristic curve from 0.71 to 0.77; χ 2 1 = 6.6; P = .01).CONCLUSIONS Personality was a powerful predictor of missing study data in this RCT. Assessing personality could inform efforts to enhance data completion and adjust analyses for bias caused by missing data. Ann Fam Med 2009;7:148-156. DOI: 10.1370/afm.920. INTRODUCTIOND espite advantages compared with observational studies, randomized controlled trials (RCTs) have limitations.1 One threat to their validity is bias resulting from nonrandom missing data. Commonly measured sociodemographic [2][3][4][5][6] and health status 7-9 variables have been associated with missing data caused by study attrition. Because such variables may also affect study outcomes, bias in the assessment of treatment effects may occur, though statistical adjustment can mitigate bias.Psychological factors also likely affect study participants' decisions to drop out from, keep data collection appointments for, or complete all questionnaire items in clinical research studies, yet they are rarely measured. This omission may be critical in assessing the validity and applicability of studies, since adherence to study protocols, including placebos, can have profound effects on outcomes, comparable to active treatment effects. [10][11][12] Although earlier studies have explored attrition resulting from psychological factors in patients with psychiatric disorders [13][14][15] [17][18][19] The result of more than 7 decades of research, 17 FFM factors are empirically derived, broad clusters of behavioral and dispositional tendencies (Table 1). They capture the major axes of psychological and beh...

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Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

Section: Per S Ona L I T Y a S Pr Edic Tor O F Mis Sing Datamentioning

confidence: 99%

mentioning

confidence: 99%

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Is Personality a Key Predictor of Missing Study Data? An Analysis From a Randomized Controlled Trial

Jerant¹,

Chapman²,

Duberstein³

et al. 2009

The Annals of Family Medicine

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Sense of coherence and self-sacrificing defense style as predictors of psychological distress and quality of life in rheumatoid arthritis: a 5-year prospective study

et al. 2014

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Individual differences in adjustment during a disease's course determine psychological response and outcome. This study aimed to investigate prospectively whether coping with health stressors and self-sacrificing defense style could predict psychological adjustment and health-related quality of life (HRQoL) in patients with rheumatoid arthritis (RA). Seventy-four consecutive RA patients attending a rheumatology clinic were assessed for psychological distress (SCL-90-R), sense of coherence (SOC scale), self-sacrificing defense style (Defense Style Questionnaire-88), disease activity (DAS-28), pain, disability (Health Assessment Questionnaire) and HRQoL (World Health Organization Quality of Life Instrument, Short Form) at baseline and 5 years later. Multiple regression and moderator analyses were carried out. The results showed that disease activity (p < .001), pain (p = .005), psychological distress (p = .031), social relations HRQoL (p = .042) and environment HRQoL (p = .020) significantly improved over time. SOC was found an independent predictor of improvement in psychological distress (p = .003), overall general health (p = .002) and social relations HRQoL (p = .004); self-sacrificing independently predicted environment HRQoL (p = .042). The self-sacrificing defense style moderated the relationships between improvement in pain and improvement in overall general health (p = .024) and between improvement in pain and improvement in social relations HRQoL (p = .006). These findings indicate that, in RA, SOC predicts improvement in psychological distress and HRQoL over time, while a self-sacrificing defense style moderates the relationship of pain with HRQoL in the long term. These variables may partly explain inter-individual differences in adaptation to RA. Therefore, the design of psychotherapeutic trials targeting the patients' defensive profiles and coping with health stressors capacities is an important research perspective.

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