Annals of Behavioral Medicine

, Volume 47, Issue 1, pp 92–101 | Cite as

Conscientiousness and Medication Adherence: A Meta-analysis

Original Article

Abstract

Background

Approximately a quarter to a half of all people fail to take their medication regimen as prescribed (i.e. non-adherence). Conscientiousness, from the five-factor model of personality, has been positively linked to adherence to medications in several recent studies.

Purpose

This study aimed to systematically estimate the strength and variability of this association across multiple published articles and to identify moderators of this relationship.

Method

A literature search identified 16 studies (N = 3,476) that met the study eligibility criteria. Estimates of effect sizes (r) obtained in these studies were meta-analysed.

Results

Overall, a higher level of conscientiousness was associated with better medication adherence (r = 0.15; 95 % CI, 0.09, 0.21). Associations were significantly stronger in younger samples (r = 0.26, 95 % CI, 0.17, 0.34; k = 7).

Conclusion

The small association between conscientiousness and medication adherence may have clinical significance in contexts where small differences in adherence result in clinically important effects.

Keywords

Adherence Compliance Personality Conscientiousness Medication 

Introduction

Most long-term medical treatments for chronic illness involve the prescription of a regimen of one or more daily medications [1]. It has been estimated that between 25 [2] and 50 % [3] of patients do not follow medical recommendations as prescribed. This has been termed non-adherence and is a primary cause of the existence of considerable efficacy–effectiveness gaps for many evidence-based medical treatments [4]. Non-adherence to medication is a complex behaviour with many diverse determinants ranging from the micro-level of individual patient beliefs about medications [5] or the complexity of the specific medical regimen [6] to the macro-level of health care organisational factors [7, 8]. One intriguing and recurring psychological explanation for the failure to follow medical advice concerns the role of personality characteristics [9, 10, 11].

There has been a particular focus on conscientiousness, one of the traits of the ‘Five-Factor model’ of personality [12, 13], with respect to the self-regulation of health-relevant behaviour [14]. Conscientiousness is defined as ‘socially prescribed impulse control that facilitates task-and goal-directed behaviour, such as thinking before acting, delaying gratification, following norms and rules and planning, organising and prioritising tasks’ ([15], p. 121). This definition has clear resonance with a number of non-trait psychological constructs relating to volitional processes that dominate the health behaviour change literature, such as action control [16] and self-regulatory strength [17, 18]. Bogg and Robert’s meta-analytic review [19] of conscientiousness and health behaviour indicates that conscientiousness is reliably associated with a range of both positive and negative behaviours that are known to be important for health and the onset of range of diseases, namely tobacco use, diet and activity patterns, excessive alcohol use, violence, risky sexual behaviour, risky driving, suicide and drug use [19].

A recent theoretical model examining the central role of traits to the disease process, suggests that disease process is influenced by health behaviours, cognitions and adherence to medical treatment [9], with traits important to the expression of these variables. In the same way that conscientiousness is a good candidate trait for the prediction of key primary prevention health behaviours [19], it should also be a good candidate trait for the prediction of secondary prevention behaviours such as medication adherence [9]. Despite the systematic study of the relationship between conscientiousness and medication adherence for almost 20 years [20], there has been no systematic evaluation of strength and variability of its contribution.

Medication taking is a qualitatively different behaviour from those examined by Bogg and Roberts [19] in at least three key respects. First, medication taking is not a behaviour that typically occurs in an interpersonal context in the way that many of the health behaviours do [19]. Such behaviours are often relatively prolonged social interactions (e.g. eating, physical activity and alcohol use) and are social interactions by definition in some cases (e.g. risky sex and violence). Second, medication taking is more often a secondary prevention behaviour in individuals where disease has been confirmed and some illness has been experienced and the aim of the medication regimen is to reduce the risk of reoccurrence of the illness or to alleviate symptoms [1]. Third, medication taking does not typically provide immediate and automatic hedonic benefits in the way that physical activity, alcohol use, unhealthy eating, smoking, risky sex and violence do. These behaviours may be more susceptible to automatic and impulsive processes [21, 22] whereas medication taking may be more strongly driven by reflective processes [23]. Therefore, the nature of the observed associations between conscientiousness and the health behaviours identified in the Bogg and Roberts review [19] cannot be assumed for medication taking.

However, there are key aspects of conscientiousness that also make it a good candidate for increasing levels of medication adherence that may be more reflective, long term and routinised. Conscientiousness is linked to planning and impulse control via diligence, perseverance, tenacity, orderliness and industriousness [24, 25, 26]. These are all qualities that are likely to be helpful with respect to remembering and planning to take medications, and also paying attention to doses and times of mediation [27]. Consistent with this conscientiousness has been shown to enhance performance on a number of cognitive and social cognitive variables linked to persistence, memory, vigilance and planning. For example, those high in conscientiousness perform better on memory tasks [28], training and transfer of training [28], attention and executive control task [24], vigilance tasks and perceptual speed [29, 30], show increased effort [31] and are more likely to enact their intentions [32]. Thus, conscientiousness in particular should influence adherence and that the main route of this influence would be through their effects on basic cognitive and social cognitive processes [9].

To date, there has been no systematic attempt to quantitatively synthesise the evidence linking conscientiousness and adherence to medication across the range of studies and methodologies that have looked at this issue. In the present study, we identify studies that have estimated the association between conscientiousness and medication adherence and perform a meta-analysis on this data to estimate the strength of this association and to identify moderators of this association. It is likely that the effects of conscientiousness on medication adherence vary according to a range of methodological factors. Therefore, we also conducted moderator analyses, which were informed by previous meta-analyses examining the association between psychological factors and adherence to treatment [33, 34].

Method

Search Strategy

ISI Web of Science (ISI WOS), PubMed and PsychInfo were searched for full published reports to the end of August 2012. The reference lists of selected studies were also searched for additional articles. The following three search strings were used initially: (1) conscientiousness and adher*, (2) conscientiousness and complian* and (3) conscientiousness and medication. We also conducted searches using the nine facets of conscientiousness identified in a recent narrative review by Bogg and Roberts [13] with the terms ‘Personality’, ‘adher*’, ‘complian*’ and ‘medication’. These facet terms were ‘orderliness’, ‘industriousness’, ‘self-control’, ‘responsibility’, ‘traditionalism’, ‘decisiveness’, ‘formality’, ‘punctuality’ and ‘persistence’. In addition citation searches within ISI WOS were performed on all papers that met the criteria for study inclusion. The search strategy was developed to identify papers examining conscientiousness as defined by the Big 5 approach [15].

Criteria for Study Inclusion

The following criteria were used to determine study inclusion: (1) The published paper was written in English, published in full-text format in a peer-review journal, and analyses were of primary data. (2) A measure of medication adherence was included using any of the following methods: self-report, serum assay, pill count, refill or prescription records and electronic monitoring. (3) A measure of conscientiousness, as defined by the Big 5 approach [15] or similar, was included. (4) A measure of the strength of the association between conscientiousness and medication adherence was included or a statement that an association did not exist was specified.

Data Extraction

An a priori data extraction form was developed, and data were coded from each paper by two coders. Any discrepancies in coding were identified and resolved by rechecking the given paper and referring to established methodological conventions in meta-analysis [35]. The following information was extracted from each included study: the study sample size, the medical condition associated with the prescribed medications, the study design, the methodology used to measure medication adherence, the measure used to assess conscientiousness, the sample demographic characteristics and the bivariate correlations (or related statistical information) between Conscientiousness and medication adherence.

Study Quality Assessment

Each study was assessed for study methodological quality using a 4-point assessment tool developed for this meta-analysis by two coders. Any discrepancies in scoring were identified and resolved by rechecking the given paper and referring to the preset criteria for assessing study quality. A point was given for each of the following four methodological criteria achieved. (1) A prospective design: this can reduce biases in effect sizes due to contemporaneous measurement of conscientiousness and medication adherence, e.g. focusing illusion effects [36]. (2) An objective measure of medication adherence was used, i.e. a measure that did not rely on self-report, as social desirability and recall biases could be minimised. (3) A sample size greater than 85 was recruited, as this is the minimum number required to have 80 % power to detect a medium effect size using r and an alpha of 0.05 [37]. This would increase the likelihood that a more reliable estimate of the association was ascertained. (4) An adjustment for age was included in the estimation of the effect size of the association of conscientiousness and medication adherence, as there is evidence that conscientiousness increases in older adulthood [38] and poorer medication adherence has been linked to age [39]. Therefore analyses that adjust for age can remove that part of the association between conscientiousness and medication adherence that may be due to developmental processes (e.g. poorer adherence in early and later life).

Statistical Analysis

The r effect size of the association between conscientiousness and medication adherence from each study was used as the primary data for the meta-analysis. This represents the strength and direction of association between the measures of adherence and the measure of conscientiousness. Positive effect sizes reflect the association of better adherence (i.e. lower non-adherence and higher levels of conscientiousness). Comprehensive Meta-analysis Version 2 software © was used to convert effect sizes into r when they were not presented in the included paper. A random effects model was used for all analysis and plots unless otherwise stated. Unadjusted r was used in all studies when available (n = 13). When a non-significant association was reported but no data was available, z = 0.00 was assigned as a conservative estimate. This was done for two studies [40, 41]. When studies used multiple measures of adherence [42] and examined several outcomes, these data points were averaged. This conservative approach has been advocated and applied in previously published meta-analytic reviews in this area [33]. When studies reported varying sample sizes for reported statistical tests the smaller sample size was used.

In order to assess the potential role of moderators in the medication adherence and conscientiousness relationship, each study was coded according to the following: sample size, study design (cross-sectional/ prospective) whether self-report only was used to measure adherence (yes/no), whether the sample was defined as a patient i.e. a particular medical diagnosis or a ‘healthy’ group i.e. primary preventive medications (yes/no), whether the NEO was used (to examine the observed associations in those studies with a homogeneous set of conscientiousness scales), study quality (0–4 scale) and average age of the sample, which was also examined as a categorical moderator (< and >50 years old). The selection of these moderators was based on previous meta-analyses of psychological factors and medication adherence [33, 34]. Publication bias was assessed both schematically using a funnel plot and statistically using Egger’s regression intercept and by calculating the failsafe number-FSN [35].

Results

Identified Studies

In total, 580 unique records were initially screened from using the search terms in the three databases. The most common reasons for paper exclusion were no medication adherence measure and no primary data. Following the assessment of these studies for eligibility and the citation searches of the detected eligible studies 16 papers were identified based on the criteria for study inclusion set out in the method section. The sixteen papers were published over a 17-year period between 1995 and 2012. The mean study quality score on the 0–4 study quality scale that assessed study design, adherence measurement, sample size and statistical adjustment for age was 1.81 with a standard deviation of 0.75 and a range of 1–3.

Meta-analysis

Table 1 presents details of the study characteristics included in the meta-analysis. The median sample size was 108 with a range of 55 to 771. Fourteen out of the 16 samples (88 %) were chronic illness samples. Eleven out of the 16 samples were prospective studies (69 %). Eight of the studies (50 %) used self-report methods only to measure medication adherence. Twelve studies (75 %) used versions of the NEO to measure conscientiousness. The mean age of the study samples was 52.63 (SD = 16.33).
Table 1

Study characteristics

Reference

Sample size

r

Controls

Medical condition

Study design

Adherence measure(s)

Conscientiousness measure

Mean age (years)

Study quality score

Axelsson et al. [74]

109

0.187

None

Asthma

Cross-sectional

Self-report

Impulsivity from HP5i

22

1

Axelsson et al. [75]

749

0.162

None

Chronic disease

Cross-sectional

Self-report

NEO-FFI

53.59

1

Bruce et al. [42]

55

0.340

None

Multiple sclerosis

Prospective (8 weeks)

Electronic monitoring, diary and self-report

NEO-FFI

43.36

2

Christensen et al. [55]

107

0.320

None

Type I diabetes mellitus

Cross-sectional

Self-report

Big 5 inventory

41.7

1

Christensen and Smith [20]

72

0.270

None

Renal dialysis

Prospective-(8 weeks)

Serum assay of phosphorus

NEO-FFI

46.39

2

Cohen et al. [40]

65

0.000

None

Depression

Prospective (14 weeks)

Electronic monitoring

NEO-PI-R

41.2

2

Dobbels et al. [76]

174

0.175

None

Heart, liver and lung transplant candidates

Cross-sectional

Self-report

NEO-FFI

52.3

1

Ediger et al. [77]

326

0.050

Age, gender, employment, diagnosis, gender*age, gender*diagnosis and gender*employment

Inflammatory bowel disease

Prospective (1 year)

Self-report

NEO-FFI

41

3

Insel et al. [78]

58

0.260

None

Community-dwelling older adults who were self-administering medications

Prospective (8 weeks)

Electronic monitoring

SFPQ-industriousness

77

2

Jerant et al. [79]

771

0.010

Neuroticism, agreeableness, extraversion and openness

Community-dwelling older adults who were participating in a RCT

Prospective (median, 6.1 years)

Pill counts

NEO-FFI

78.6

3

Moran et al. [80]

56

−0.090

Previous transplant failure, social support and the interaction term for social support and C

Hemodialysis

Prospective (8 weeks)

Serum assay of phosphorus

NEO-FFI

57.2

2

O’ Cleirigh et al. [53]

91

0.370

None

HIV positive

Prospective (1 year)

Self-report

NEO-FFI

37.9

2

Penedo et al. [41]

116

0.000

None

HIV/AIDS

Cross-sectional

Self-report

NEO-PI-R

39.2

1

Quine et al. [81]

537

0.150

None

Hypertension

Prospective (8 weeks)

Self-report

International personality item pool

69

2

Stilley et al. [82]

158

0.240

None

LDL serum cholesterol levels of 160 mg/dl or higher

Prospective (24 weeks)

Electronic monitoring

NEO-PI-R

46.2

3

Wiebe and Christensen [83]

65

0.040

None

Hemodialysis

Prospective (8 weeks)

Serum assay of phosphorus

NEO-FFI

56

1

HP5i The Health-Relevant Personality 5 Factor Inventory, NEO-FFI The Neuroticism, Extraversion, and Openness to Experience, Five Factor Inventory, NEO-PI-R The revised NEO Personality Inventory, SFPQ Six-Factor Personality Questionnaire, C Conscientiousness

The overall average weighted correlation coefficient across the 16 studies was r = 0.12 (p < 0.001) using a fixed effects model and r = 0.15 (p < 0.001) using a random effects model, which is presented in the forest plot in Fig. 1. This figure represented as an odds ratio using the random effects model was 1.71 (95 % CI, 1.37, 2.14) and 0.30 (95 % CI, 0.17, 0.42) represented as a standardised difference in means. Post hoc power analysis reveals that a sample size of 346 would be required to have 80 % power to detect an effect of this size with a two tailed alpha level of .05. Only three studies therefore were adequately powered to detect this size of an effect. The effect was robust with the failsafe N calculated as 217 null studies required to make the p value greater than 0.05. There was significant moderate heterogeneity around the mean effect size in the observed studies (Q = 38.37, p < 0.01; I2 = 60.90). Figure 2 presents a funnel plot of the effect sizes observed in the included 16 studies. Egger’s regression intercept indicated no evidence for publication bias in the identified studies (1.13; 95 % CI, −0.67, 2.92; p = 0.20).
Fig. 1

Forest plot of the observed associations between conscientiousness and medication adherence

Fig. 2

Funnel plot of the 16 included studies

Meta-Regression Analyses

Random effects meta-regression, using the moment method [35], revealed that larger sample sizes (Z = −1.21, p = 0.22) and higher study methodological quality (Z = −0.80, p = 0.42) were not associated with observed effect sizes. An older sample average age (Z = −2.11, p = 0.03) was associated with significantly smaller effect sizes.

Categorical Moderators

Table 2 provides a summary of the meta-analysis by potential categorical moderators of the Conscientiousness and medication adherence association. Medication adherence measurement (Q = 0.408, df = 1, p = 0.52), conscientiousness measurement (Q = 1.573, df = 1, p = 0.21), study design (Q = 0.15, df = 1, p = 0.70) and sample type (Q = 0.546, df = 1, p = 0.46) were not significant moderators of the conscientiousness and medication adherence association according to the between-group test of heterogeneity in the random effects model. Age (Q = 7.695, df = 1, p = 0.006) and whether statistical controls were used in the analysis (Q = 11.371, df = 1, p = 0.001) did emerge as statistically significant moderators of the Conscientiousness and medication adherence association. The association was significantly stronger in studies with a mean age less than 50 years old and in studies that did not include adjustments for covariates.
Table 2

Summary of potential categorical moderators of the conscientiousness and medication adherence association

Moderator

Number

k

r (95 % CI)

Z

P value

FSN

Egger’s intercept

Medication adherence measurement

  Self-report only (yes)

2,186

8

0.164 (0.086, 0.240)

4.100

<0.001

98

1.12

  Self-report only (no)

1,290

8

0.125 (0.029, 0.218)

2.560

0.010

18

1.51

Conscientiousness measurement

  NEO

2,665

12

0.126 (0.056, 0.195)

3.507

<0.001

84

0.90

  Other measure

811

4

0.214 (0.094, 0.327)

3.474

0.001

27

1.65

Study design

  Cross-sectional

1,255

5

0.165 (0.061, 0.266)

3.095

0.002

34

0.30

  Prospective

2,221

11

0.140 (0.062, 0.216)

3.528

<0.001

72

1.47

Sample type

  Patient samples

2,547

14

0.158 (0.093, 0.221)

4.736

<0.001

171

0.34

  Healthy samples

929

2

0.100 (−0.042, 0.237)

1.383

0.167

Mean age of sample

  Less than 50 years old

626

7+

0.255 (0.166, 0.340)

5.490

<0.001

68

−0.73

  Greater than 50 years old

2,524

8

0.098 (0.031, 0.164)

2.865

0.004

31

−0.22

Controls used in analysis

  Yes r adjusted

1,130

3

0.015 (−0.068, 0.098)

0.353

0.724

0

−0.63

  No r unadjusted

2,346

13

0.182 (0.132, 0.232)

6.996

<0.001

213

0.70

+One study [77] was excluded as the r estimate from this study included an adjustment for age

Discussion

This meta-analysis provides four important new findings. First the results confirm that greater conscientiousness is associated with better medication adherence, which gives increased confidence in the validity of early observations [20]. Second, the magnitude of this association (r = 0.15) is comparable to better established and clinically acknowledged [34] psychological predictors of poor medication adherence such as depression which has been recently estimated as r = −0.16 in a meta-analysis of 31 studies and 18,245 participants in the USA [43]. Third, the moderation analysis revealed that the association between conscientiousness and medication adherence was stronger in younger samples and in analyses where there were no adjustments for covariates. This suggests that conscientiousness may be particularly important for understanding poor adherence earlier in the lifespan and that there are likely to be a number of important mediators and moderators of this relationship. Fourth, the association does not appear to be an artefact of self-report biases as there was no observed moderating effect for type of measurement used to assess medication adherence.

As conscientiousness has been linked to better survival in observational studies [12, 44, 45, 46, 47], better medication adherence may partly explain this association, particularly in patient samples where medication can play an important part in optimising secondary prevention of illness [46]. One recent study provides support for these hypotheses by showing that self-efficacy for medication adherence can account for the association between conscientiousness and perceived health among older adults [48]. This kind of mediation analysis provides information for developing behaviour change techniques to enhance adherence to medications in those with chronic illness, as key modifiable mechanisms are identified [49, 50].

The overall summary effect size observed in this analysis was in the small range according to Cohen’s criteria [37]. Therefore, it is important to acknowledge that the amount of variability that it can account for is relatively small at approximately 2 %. This is perhaps not surprising given the complexity of the behaviour of medication taking [2]. It is worth considering that while the effect sizes may be small, the clinical impact may be large if small differences in adherence can result in clinically significant effects. For example, increasing adherence by one anti-hypertensive pill per week for a once a day regimen reduces the hazard of stroke by 8–9 % and death by 7 % [51] and small deviations from the prescribed medication regimen of warfarin, a highly efficacious anticoagulant, can result in immediate and substantial clinical risk to patients prescribed this medication [52]. Medications such as this that carry substantial risk may be less suitable for those who have lower levels of conscientiousness and equally medications that require very high levels of adherence, such as highly active antiretroviral therapies [53], to achieve efficacy may be less effective in those lower in conscientiousness due to poor adherence.

The effect sizes also have to be understood within the wider theoretical framework [9] that predicts that conscientiousness will influence adherence via cognitive processes (e.g. memory) [27] and social cognitive processes (e.g. intentions and self-efficacy) which are known determinants of medication adherence [11]. Thus, the effect sizes reported here are likely to represent either the total or direct effects and there may still be indirect routes via these cognitive and social cognitive processes. Furthermore, the model [9] also indicates that conscientiousness has a direct effect on health behaviour [19]. Thus, the small effect size should not be seen to indicate that there is not a central role for conscientiousness in understanding health outcomes more generally. This meta-analysis reflects the average linear effects that differ between individuals rather than the nonlinear interactions of conscientiousness with other variables within individuals [54].

An important consideration relates to whether conscientiousness (and traits in general) provides useful information to health care professionals. If as detailed above conscientiousness is linked to behaviours that influence both medication adherence and behaviours that can influence the effectiveness of medications, e.g. alcohol consumption, then knowing that someone is low in conscientiousness is important clinically [9], particularly if it provides information on an individual’s likelihood of benefiting or being harmed from a treatment, i.e. those low on conscientiousness may take too little or too much of their medication resulting in a lack of treatment benefit or in some instances increased risk of harm [52]. This information can be used to trigger questions about lifestyle and start appropriate interventions. It is possible that some of the shorter indices of conscientiousness [55] can be easily administered as part of a time-constrained clinical interaction, as the number of items included are similar to instruments used to assess depressive symptomatology in clinical practice [56]. However at present there are no defined ways to categorise low versus high conscientiousness. While taxometric analysis of conscientiousness have not been conducted recent narrative reviews suggest that it is likely to be continuous [57], as are other personality traits related to health [58, 59]. Latent profile analyses or ROC curve analyses may be ways forward to identify how levels of a trait (and conscientiousness in particular) are linked to adherence [60]. Therefore, at present for clinicians levels of conscientiousness should be used as an additional piece of information to guide and inform practice, maybe relative to established norms, rather than as a diagnostic [9].

Where patients are identified as lower in conscientiousness certain behaviour change techniques [61] could be used to enhance adherence to medications. For example, recent randomised controlled trials of very simple planning interventions have led to significant improvements in medication adherence among patients with epilepsy and patients following stroke, who were having difficulty with taking their medication as prescribed [62, 63]. There is recent evidence however indicating that there are individual differences in the capacity to make plans, therefore there may be trait level moderators of the effectiveness of some of these interventions approaches [64]. Theoretically, one would expect that certain behaviour change techniques that engage more reflective process might be less effective for those lower in conscientiousness, e.g. goal setting, comparison of outcomes and shaping knowledge [65], as these require capacities that may be, by definition, weaker in this group, e.g. the conscientiousness facets of orderliness, self-control, decisiveness and persistence [13].

Finally, there is a growing theoretical [9, 66] and empirical literature [67, 68] indicating that normal personality traits can change as a function of pharmaceutical [67] and behavioural interventions [68]. As such, clinicians and practitioners should not see traits as fixed but realise that interventions and medications may also influence the trait and as such traits should be measured across the time course of illness and intervention [9].

There are a number of limitations to this analysis which should be acknowledged. First, the available observational data did not allow us to make causal inferences or to examine whether particular facets of conscientiousness [26], e.g. Industriousness and Orderliness, were associated with medication adherence, as the data on these subcomponents was not provided in enough of the reviewed studies. It is possible that medication adherence may be more or less associated with the facets that comprise the higher order personality factor of conscientiousness. Second, in relation to the medication adherence measures we were unable to distinguish between intentional and unintentional non-adherence, as none of the included studies had separate measures. It is increasingly recognised that this is an important distinction to make [69] given the differing role of motivational and volitional processes in each kind of non-adherence [63]. Finally, it has argued theoretically [9] and been demonstrated empirically that the personality [70, 71] of others in one’s immediate ongoing social environment, e.g. partner or one’s doctor, may have important effects on health and health relevant behaviour. For example, a health protective effect has been observed when one’s spouse has higher levels of conscientiousness in a large sample of older adult couples in the USA [70]. None of the studies in the present meta-analysis examined this ‘compensatory conscientiousness’ phenomenon, which may be linked to better medication adherence, if one person in an ongoing stable relationship directs health related behaviour for both members of a dyad [72]. Future multilevel studies can examine the extent to which dyad-level conscientiousness is critical for good medication adherence and whether medication adherence is best considered a behaviour that is regulated within ongoing social relationship as some recent work has suggested, e.g. patient–informal carer dyads [73].

Conclusions

Conscientiousness accounts for a significant proportion of the variability in the extent to which people adhere to medications. Future studies that identify the modifiable processes that explain this link (e.g. cognitive and social cognitive processes) and the key moderators of these processes may help in the design of interventions to enhance medication adherence.

Notes

Conflict of Interest

The authors have no conflict of interest to disclose.

References

  1. 1.
    Brown MT, Bussell JK. Medication adherence: WHO cares? Mayo Clin Proc. 2011;86:304-314.PubMedCrossRefGoogle Scholar
  2. 2.
    DiMatteo MR. Variations in patients’ adherence to medical recommendations: A quantitative review of 50 years of research. Med Care. 2004;42:200-209.PubMedCrossRefGoogle Scholar
  3. 3.
    Sabaté E. Adherence to long-term therapies: Evidence for action. Geneva: WHO; 2003.Google Scholar
  4. 4.
    DiMatteo MR, Giordani PJ, Lepper HS, Croghan TW. Patient adherence and medical treatment outcomes: A meta-analysis. Med Care. 2002;40:794-811.PubMedCrossRefGoogle Scholar
  5. 5.
    O’Carroll R, Whittaker J, Hamilton B, et al. Predictors of adherence to secondary preventive medication in stroke patients. Ann Behav Med. 2011;41:383-390.PubMedCrossRefGoogle Scholar
  6. 6.
    Claxton AJ, Cramer J, Pierce C. A systematic review of the associations between dose regimens and medication compliance. Clin Ther. 2001;23:1296-1310.PubMedCrossRefGoogle Scholar
  7. 7.
    Cutler DM, Everett W. Thinking outside the pillbox-medication adherence as a priority for health care reform. N Engl J Med. 2010;362:1553-1555.PubMedCrossRefGoogle Scholar
  8. 8.
    Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005;353:487-497.PubMedCrossRefGoogle Scholar
  9. 9.
    Ferguson E. Personality is of central concern to understand health:towards a theoretical model for health psychology. Health Psych Rev. 2013;7:S32-S70.Google Scholar
  10. 10.
    Friedman HS. Long-term relations of personality and health: Dynamisms, mechanisms, tropisms. J Pers. 2000;68:1089-1107.PubMedCrossRefGoogle Scholar
  11. 11.
    Molloy GJ, Randall G, Wikman A, et al. Type D personality, self-efficacy, and medication adherence following an acute coronary syndrome. Psychosom Med. 2012;74:100-106.PubMedCrossRefGoogle Scholar
  12. 12.
    Martin LR, Friedman HS, Schwartz JE. Personality and mortality risk across the life span: The importance of conscientiousness as a biopsychosocial attribute. Health Psychol. 2007;26:428-436.PubMedCrossRefGoogle Scholar
  13. 13.
    Bogg T, Roberts BW. The case for conscientiousness: Evidence and implications for a personality trait marker of health and longevity. Ann Behav Med. 2013;45:278-288.PubMedCrossRefGoogle Scholar
  14. 14.
    Lodi-Smith J, Jackson J, Bogg T, et al. Mechanisms of health: Education and health-related behaviours partially mediate the relationship between conscientiousness and self-reported physical health. Psychol Health. 2010;25:305-319.PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    John OP, Srivastava S. The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In: Pervin LA, John OP, eds. Handbook of personality. Theory & research. London: The Guilford Press; 1999:102-138.Google Scholar
  16. 16.
    Sniehotta FF, Nagy G, Scholz U, Schwarzer R. The role of action control in implementing intentions during the first weeks of behaviour change. Brit J Soc Psychol. 2006;45:87-106.CrossRefGoogle Scholar
  17. 17.
    Hofmann W, Baumeister RF, Forster G, Vohs KD. Everyday temptations: An experience sampling study of desire, conflict, and self-control. J Pers Soc Psychol. 2012;102:1318-1335.PubMedCrossRefGoogle Scholar
  18. 18.
    Daly M, Baumeister RF, Delaney L, Maclachlan M. Self-control and its relation to emotions and psychobiology: Evidence from a Day Reconstruction Method study. J Behav Med. In pressGoogle Scholar
  19. 19.
    Bogg T, Roberts BW. Conscientiousness and health-related behaviors: A meta-analysis of the leading behavioral contributors to mortality. Psychol Bull. 2004;130:887-919.PubMedCrossRefGoogle Scholar
  20. 20.
    Christensen AJ, Smith TW. Personality and patient adherence: Correlates of the five-factor model in renal dialysis. J Behav Med. 1995;18:305-313.PubMedCrossRefGoogle Scholar
  21. 21.
    Marteau TM, Hollands GJ, Fletcher PC. Changing human behavior to prevent disease: The importance of targeting automatic processes. Science. 2012;337:1492-1495.PubMedCrossRefGoogle Scholar
  22. 22.
    Sheeran P, Gollwitzer PM, Bargh JA. Nonconscious Processes and Health. Health Psychol. 2013;32:460-473.Google Scholar
  23. 23.
    Strack F, Deutsch R. Reflective and impulsive determinants of social behavior. Pers Soc Psychol Rev. 2004;8:220-247.PubMedCrossRefGoogle Scholar
  24. 24.
    Matthews G, Zeidner M. Individual differences in attentional networks: Trait and state correlates of the ANT. Pers Individ Dif. 2012;53:574-579.CrossRefGoogle Scholar
  25. 25.
    Costa PT, McCrae RR. NEO PI-R professional manual. Odessa: Psychological Assessment Resources, Inc; 1992.Google Scholar
  26. 26.
    DeYoung CG, Quilty LC, Peterson JB. Between facets and domains: 10 aspects of the Big Five. J Pers Soc Psychol. 2007;93:880-896.PubMedCrossRefGoogle Scholar
  27. 27.
    Zogg JB, Woods SP, Sauceda JA, Wiebe JS, Simoni JM. The role of prospective memory in medication adherence: A review of an emerging literature. J Behav Med. 2012;35:47-62.PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Studer-Luethi B, Jaeggi SM, Buschkuehl M, Perrig WJ. Influence of neuroticism and conscientiousness on working memory training outcome. Pers Individ Dif. 2012;53:44-49.CrossRefGoogle Scholar
  29. 29.
    Rose CL, Murphy LB, Byard L, Nikzad K. The role of the big five personality factors in vigilance performance and workload. Eur J Pers. 2002;16:185-200.CrossRefGoogle Scholar
  30. 30.
    Ackerman PL, Heggestad ED. Intelligence, personality, and interests: Evidence for overlapping traits. Psychol Bull. 1997;121:219-245.PubMedCrossRefGoogle Scholar
  31. 31.
    Fong EA, Tosi HL. Effort, performance, and conscientiousness: An agency theory perspective. J Manag. 2007;33:161-179.Google Scholar
  32. 32.
    Chatzisarantis NLD, Hagger MS. Influences of personality traits and continuation intentions on physical activity participation within the theory of planned behaviour. Psychol Health. 2008;23:347-367.CrossRefGoogle Scholar
  33. 33.
    DiMatteo MR. Social support and patient adherence to medical treatment: A meta-analysis. Health Psychol. 2004;23:207-218.PubMedCrossRefGoogle Scholar
  34. 34.
    DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: Meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med. 2000;160:2101-2107.PubMedCrossRefGoogle Scholar
  35. 35.
    Borenstein M. Introduction to meta-analysis. Oxford: Wiley; 2009.CrossRefGoogle Scholar
  36. 36.
    Kahneman D, Krueger AB, Schkade D, Schwarz N, Stone AA. Would you be happier if you were richer? A focusing illusion. Science. 2006;312:1908-1910.PubMedCrossRefGoogle Scholar
  37. 37.
    Cohen J. A power primer. Psychol Bull. 1992;112:155-159.PubMedCrossRefGoogle Scholar
  38. 38.
    Roberts BW, Walton KE, Bogg T. Conscientiousness and health across the life course. Rev Gen Psychol. 2005;9:156-168.CrossRefGoogle Scholar
  39. 39.
    DiMatteo MR, Haskard KB, Williams SL. Health beliefs, disease severity, and patient adherence: A meta-analysis. Med Care. 2007;45:521-528.PubMedCrossRefGoogle Scholar
  40. 40.
    Cohen NL, Ross EC, Bagby RM, Farvolden P, Kennedy SH. The 5-factor model of personality and antidepressant medication compliance. Can J Psychiatry. 2004;49:106-113.PubMedGoogle Scholar
  41. 41.
    Penedo FJ, Gonzalez JS, Dahn JR, et al. Personality, quality of life and HAART adherence among men and women living with HIV/AIDS. J Psychosom Res. 2003;54:271-278.PubMedCrossRefGoogle Scholar
  42. 42.
    Bruce JM, Hancock LM, Arnett P, Lynch S. Treatment adherence in multiple sclerosis: Association with emotional status, personality, and cognition. J Behav Med. 2010;33:219-227.PubMedCrossRefGoogle Scholar
  43. 43.
    Grenard JL, Munjas BA, Adams JL, et al. Depression and medication adherence in the treatment of chronic diseases in the United States: A meta-analysis. J Gen Intern Med. 2011;26:1175-1182.PubMedCentralPubMedCrossRefGoogle Scholar
  44. 44.
    Friedman HS, Tucker JS, Tomlinson-Keasey C, et al. Does childhood personality predict longevity? J Pers Soc Psychol. 1993;65:176-185.PubMedCrossRefGoogle Scholar
  45. 45.
    Hagger-Johnson G, Sabia S, Nabi H, et al. Low conscientiousness and risk of all-cause, cardiovascular and cancer mortality over 17 years: Whitehall II cohort study. J Psychosom Res. 2012;73:98-103.PubMedCrossRefGoogle Scholar
  46. 46.
    Christensen AJ, Ehlers SL, Wiebe JS, et al. Patient personality and mortality: A 4-year prospective examination of chronic renal insufficiency. Health Psychol. 2002;21:315-320.PubMedCrossRefGoogle Scholar
  47. 47.
    Hill PL, Turiano NA, Hurd MD, Mroczek DK, Roberts BW. Conscientiousness and longevity: An examination of possible mediators. Health Psychol. 2011;30:536-541.PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Hill PL, Roberts BW. The role of adherence in the relationship between conscientiousness and perceived health. Health Psychol. 2011;30:797-804.PubMedCentralPubMedCrossRefGoogle Scholar
  49. 49.
    Molloy GJ, O’Carroll RE, Witham MD, McMurdo ME. Interventions to enhance adherence to medications in patients with heart failure: A systematic review. Circ Heart Fail. 2012;5:126-133.PubMedCrossRefGoogle Scholar
  50. 50.
    Haynes RB, Ackloo E, Sahota N, McDonald HP, Yao X. Interventions for enhancing medication adherence. Cochrane Database Syst Rev. 2008:CD000011.Google Scholar
  51. 51.
    Bailey JE, Wan JY, Tang J, Ghani MA, Cushman WC. Antihypertensive medication adherence, ambulatory visits, and risk of stroke and death. J Gen Intern Med. 2010;25:495-503.PubMedCentralPubMedCrossRefGoogle Scholar
  52. 52.
    Kimmel SE, Chen Z, Price M, et al. The influence of patient adherence on anticoagulation control with warfarin: Results from the International Normalized Ratio Adherence and Genetics (IN-RANGE) Study. Arch Intern Med. 2007;167:229-235.PubMedCrossRefGoogle Scholar
  53. 53.
    O’Cleirigh C, Ironson G, Weiss A, Costa PT. Conscientiousness predicts disease progression (CD4 number and viral load) in people living with HIV. Health Psychol. 2007;26:473-480.PubMedCrossRefGoogle Scholar
  54. 54.
    O’Connor DB, Conner M, Jones F, McMillan B, Ferguson E. Exploring the benefits of conscientiousness: An investigation of the role of daily stressors and health behaviors. Ann Behav Med. 2009;37:184-196.PubMedCrossRefGoogle Scholar
  55. 55.
    Christensen AJ, Moran PJ, Wiebe JS. Assessment of irrational health beliefs: Relation to health practices and medical regimen adherence. Health Psychol. 1999;18:169-176.PubMedCrossRefGoogle Scholar
  56. 56.
    Doyle F, McGee HM, De La Harpe D, Shelley E, Conroy R. The Hospital Anxiety and Depression Scale depression subscale, but not the Beck Depression Inventory-Fast Scale, identifies patients with acute coronary syndrome at elevated risk of 1-year mortality. J Psychosom Res. 2006;60:461-467.PubMedCrossRefGoogle Scholar
  57. 57.
    Haslam N, Holland E, Kuppens P. Categories versus dimensions in personality and psychopathology: A quantitative review of taxometric research. Psychol Med. 2012;42:903-920.PubMedCrossRefGoogle Scholar
  58. 58.
    Ferguson E, Williams L, O’Connor RC, et al. A taxometric analysis of type-D personality. Psychosom Med. 2009;71:981-986.PubMedCrossRefGoogle Scholar
  59. 59.
    Ferguson E. A taxometric analysis of health anxiety. Psychol Med. 2009;39:277-285.PubMedCrossRefGoogle Scholar
  60. 60.
    Martel MM, Goth-Owens T, Martinez-Torteya C, Nigg JT. A person-centered personality approach to heterogeneity in attention-deficit/hyperactivity disorder (ADHD). J Abnorm Psychol. 2010;119:186-196.PubMedCentralPubMedCrossRefGoogle Scholar
  61. 61.
    Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol. 2008;27:379-387.PubMedCrossRefGoogle Scholar
  62. 62.
    Brown I, Sheeran P, Reuber M. Enhancing antiepileptic drug adherence: A randomized controlled trial. Epilepsy Behav. 2009;16:634-639.PubMedCrossRefGoogle Scholar
  63. 63.
    O’Carroll RE, Chambers JA, Dennis M, Sudlow C, Johnston M. Improving adherence to medication in stroke surviviors: A pilot randomised controlled trial. Ann Behav Med. In press.Google Scholar
  64. 64.
    Allan JL, Sniehotta FF, Johnston M. The best laid plans: Planning skill determines the effectiveness of action plans and implementation intentions. Ann Behav Med. In press .Google Scholar
  65. 65.
    Michie S, Richardson M, Johnston M, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Ann Behav Med. In press.Google Scholar
  66. 66.
    Roberts BW, Jackson JJ. Sociogenomic personality psychology. J Pers. 2008;76:1523-1544.PubMedCentralPubMedCrossRefGoogle Scholar
  67. 67.
    Tang TZ, DeRubeis RJ, Hollon SD, et al. Personality change during depression treatment: A placebo-controlled trial. Arch Gen Psychiatry. 2009;66:1322-1330.PubMedCentralPubMedCrossRefGoogle Scholar
  68. 68.
    Jackson JJ, Thoemmes F, Jonkmann K, Ludtke O, Trautwein U. Military training and personality trait development: Does the military make the man, or does the man make the military? Psychol Sci. 2012;23:270-277.PubMedCrossRefGoogle Scholar
  69. 69.
    Griva K, Davenport A, Harrison M, Newman SP. Non-adherence to immunosuppressive medications in kidney transplantation: Intent vs. forgetfulness and clinical markers of medication intake. Ann Behav Med. 2012;44:85-93.PubMedCrossRefGoogle Scholar
  70. 70.
    Roberts BW, Smith J, Jackson JJ, Edmonds G. Compensatory conscientiousness and health in older couples. Psychol Sci. 2009;20:553-559.PubMedCentralPubMedCrossRefGoogle Scholar
  71. 71.
    Christensen AJ, Howren MB, Hillis SL, et al. Patient and physician beliefs about control over health: Association of symmetrical beliefs with medication regimen adherence. J Gen Intern Med. 2010;25:397-402.PubMedCentralPubMedCrossRefGoogle Scholar
  72. 72.
    Umberson D. Gender, marital status and the social control of health behavior. Soc Sci Med. 1992;34:907-917.PubMedCrossRefGoogle Scholar
  73. 73.
    Trivedi RB, Bryson CL, Udris E, Au DH. The influence of informal caregivers on adherence in COPD patients. Ann Behav Med. 2012;44:66-72.PubMedCrossRefGoogle Scholar
  74. 74.
    Axelsson M, Emilsson M, Brink E, et al. Personality, adherence, asthma control and health-related quality of life in young adult asthmatics. Respir Med. 2009;103:1033-1040.PubMedCrossRefGoogle Scholar
  75. 75.
    Axelsson M, Brink E, Lundgren J, Lotvall J. The influence of personality traits on reported adherence to medication in individuals with chronic disease: An epidemiological study in west sweden. Plos One. 2011;6.Google Scholar
  76. 76.
    Dobbels F, Vanhaecke J, Desmyttere A, et al. Prevalence and correlates of self-reported pretransplant nonadherence with medication in heart, liver, and lung transplant candidates. Transplantation. 2005;79:1588-1595.PubMedCrossRefGoogle Scholar
  77. 77.
    Ediger JP, Walker JR, Graff L, et al. Predictors of medication adherence in inflammatory bowel disease. Am J Gastroenterol. 2007;102:1417-1426.PubMedCrossRefGoogle Scholar
  78. 78.
    Insel KC, Reminger SL, Hsiao CP. The negative association of independent personality and medication adherence. J Aging Health. 2006;18:407-418.PubMedCrossRefGoogle Scholar
  79. 79.
    Jerant A, Chapman B, Duberstein P, Robbins J, Franks P. Personality and medication non-adherence among older adults enrolled in a six-year trial. Br J Health Psychol. 2011;16:151-169.PubMedCentralPubMedCrossRefGoogle Scholar
  80. 80.
    Moran PJ, Christensen AJ, Lawton WJ. Social support and conscientiousness in hemodialysis adherence. Ann Behav Med. 1997;19:333-338.PubMedCrossRefGoogle Scholar
  81. 81.
    Quine L, Steadman L, Thompson S, Rutter DR. Adherence to anti-hypertensive medication: Proposing and testing a conceptual model. Br J Health Psychol. 2012;17:202-219.PubMedCrossRefGoogle Scholar
  82. 82.
    Stilley CS, Sereika S, Muldoon MF, Ryan CM, Dunbar-Jacob J. Psychological and cognitive function: Predictors of adherence with cholesterol lowering treatment. Ann Behav Med. 2004;27:117-124.PubMedCrossRefGoogle Scholar
  83. 83.
    Wiebe JS, Christensen AJ. Health beliefs, personality, and adherence in hemodialysis patients: An interactional perspective. Ann Behav Med. 1997;19:30-35.PubMedCrossRefGoogle Scholar

Copyright information

© The Society of Behavioral Medicine 2013

Authors and Affiliations

  • G. J. Molloy
    • 1
  • R. E. O’Carroll
    • 2
  • E. Ferguson
    • 3
  1. 1.School of Psychology, National University of Ireland GalwayGalwayIreland
  2. 2.Psychology, School of Natural Sciences, University of StirlingStirlingUK
  3. 3.School of Psychology, University of NottinghamNottinghamUK

Personalised recommendations