RESEARCH ARTICLE

Depression, distress and self-efficacy: The

impact on diabetes self-care practices
Cassidy Devarajooh*, Karuthan Chinna
Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Jalan Universiti,
Wilayah Persekutuan, Kuala Lumpur, Malaysia

These authors contributed equally to this work.

* cassdeva@hotmail.com

Abstract
a1111111111 The prevalence of type 2 diabetes is increasing in Malaysia, and people with diabetes have
a1111111111
been reported to suffer from depression and diabetes distress which influences their self-
a1111111111
a1111111111 efficacy in performing diabetes self-care practices. This interviewer administered, cross sec-
a1111111111 tional study, conducted in the district of Hulu Selangor, Malaysia, involving 371 randomly
selected patients with type 2 diabetes, recruited from 6 health clinics, aimed to examine a
conceptual model regarding the association between depression, diabetes distress and
self-efficacy with diabetes self-care practices using the partial least square approach of
OPEN ACCESS structural equation modeling. In this study, diabetes self-care practices were similar regard-
Citation: Devarajooh C, Chinna K (2017)
less of sex, age group, ethnicity, education level, diabetes complications or type of diabetes
Depression, distress and self-efficacy: The impact medication. This study found that self-efficacy had a direct effect on diabetes self-care prac-
on diabetes self-care practices. PLoS ONE 12(3): tice (path coefficient = 0.438, p<0.001). Self-care was not directly affected by depression
e0175096. https://doi.org/10.1371/journal.
and diabetes distress, but indirectly by depression (path coefficient = -0.115, p<0.01) and
pone.0175096
diabetes distress (path coefficient = -0.122, p<0.001) via self-efficacy. In conclusion, to
Editor: Mohammad Ebrahim Khamseh, Institute of
improve self-care practices, effort must be focused on enhancing self-efficacy levels, while
Endocrinology and Metabolism, ISLAMIC
REPUBLIC OF IRAN not forgetting to deal with depression and diabetes distress, especially among those with
poorer levels of self-efficacy.
Received: January 9, 2017

Accepted: March 20, 2017

Published: March 31, 2017

Copyright: 2017 Devarajooh, Chinna. This is an

open access article distributed under the terms of
Introduction
the Creative Commons Attribution License, which
permits unrestricted use, distribution, and Diabetes mellitus is a common chronic disease in Malaysia. According to national studies, the
reproduction in any medium, provided the original prevalence of diabetes has increased from 11.6% in 2006 to 15.2% in 2011 [1]. People with dia-
author and source are credited.
betes suffer from a higher burden of psychosocial problems and psychological disorders [2].
Data Availability Statement: All relevant data are The prevalence of depression is higher among people with diabetes, and is partly attributed by
within the paper and its Supporting Information vascular damage which may induce cerebral pathology that constitutes vulnerability for
files.
depression [3]. Depression adds to the burden of managing diabetes, as those with depression
Funding: The authors received no specific funding perform poorer diabetes self-care [4].
for this work. Diabetes distress, an affective disorder, is a syndrome comprised of a multidimensional
Competing interests: The authors have declared component, such as worry, conflict, frustration, and discouragement that can accompany liv-
that no competing interests exist. ing with diabetes, and is closely related to depression [5]. Majority of people with diabetes who

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 Factors influencing diabetes self-care

Fig 1. Hypothesized model of the relationship between depression, diabetes distress and self
efficacy with self-care practices.
https://doi.org/10.1371/journal.pone.0175096.g001

were depressed experienced diabetes distress, however, most of those experiencing diabetes
distress were not depressed [6]. Diabetes distress effects an individuals problem solving skill
which is required to carry out diabetes self-care and this may result in poorer self-care prac-
tices, and ultimately poorer glycemic control [7].
Both depression [8]and diabetes distress [9] influences self-efficacy. A high level of self-effi-
cacy is needed to manage the daily challenges associated with caring for diabetes. Individuals
with higher levels of self-efficacy perform better diabetes self-care practices [10, 11].
This study aims to explore the relationship between depression, diabetes distress and self-
efficacy with diabetes self-care practices. Up to date, there has been no study in Malaysia
which assessed the structural relationship between depression, diabetes distress and self-effi-
cacy with diabetes self-care practices. Based on the available literature, it is hypothesized that
self-efficacy affects diabetes self-care directly, while depression and diabetes distress both have
direct and indirect effects via self-efficacy on diabetes self-care. Diabetes distress is hypothe-
sized to affect depression directly. Fig 1 illustrates the relationship between self-care with
depression, self-efficacy and distress.

Materials and methods

This was a cross sectional study with patients recruited from all 6 primary health clinics in the
district of Hulu Selangor. Hulu Selangor is the biggest district in the state of Selangor, measur-
ing about 174,047 hectares. In the district of Hulu Selangor, there were 6,396 patients with
type 2 diabetes receiving treatment in 6 government health clinics. The fees for each visit inclu-
sive of consultation, investigation and medication is only 1 Ringgit Malaysia (1 US Dollar = 4.40
Ringgit Malaysia, average exchange rate in December 2016). Eligibility criteria as a participant
in this study was being a Malaysian older than 18 years old, having a diagnosis of type 2 diabe-
tes and can at least understand the Malay language. The exclusion criteria were pregnancy and
cognitive impairment such as dementia or mental retardation. Eligible patients were
approached for written consent for the study.

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 Factors influencing diabetes self-care

Sample size
To perform a partial least square structural equation modeling, Henseler et al. [12] recom-
mended a 10 to 1 ratio of sample size to model parameter. The theoretical model in this study
had 6 model parameter. Thus with a ratio of 10 to 1, the sample size required was 60. For a reli-
able analysis, a minimal sample size of 200 is considered good. To determine diabetes self-care
practice, the sample size was calculated using the Open Epi software version 3.01. With a type
2 diabetic population of 6,396, power of 80%, confidence interval of 95% and an anticipated
frequency of good self-care at 52% [13], the required sample size was 361. The sample size was
increased by 30% after considering non-responders. The final sample size was 480 patients. A
proportionate number of patients were selected from all 6 clinics based on the number of
patient attendees. Every 10th patient on the follow-up list was approached to participate in this
study. The purpose and relevance of the study was explained to all the potential participants.

Data management and statistical analysis

This was an interviewer-based study. Data was double entered and cleaned before analysis.
The Statistical Package for the Social Science (SPSS) version 20 was used for descriptive and
inferential analysis and subsequently for factor analysis of the diabetes distress scale.
Categorical variables were presented as frequency (n) and percentages (%), and numerical
variables were presented as mean and standard deviation (SD). ANOVA and t test were used
to determine differences in continuous data.
For factor analysis, a good factor analytical model must have several properties. The guide-
lines provided by Hair et al (2010) were used [14]. The item correlation must be between 0.3
0.9, the Kaiser-Meyer-Olkin (KMO)>0.6 and the factor loading ideally >0.7 but not less than
0.5 is acceptable. The preferred Average variance extracted (AVE) is >50%, but may be less if
some factor loading are <0.7. The correlation between subdomains of the diabetes distress
scale should be<0.85 to have discriminant validity.
The Smart PLS3 software was used for the structural equation modeling. The path coeffi-
cients were calculated between variables and the significance level was set as p<0.05.

Ethical issue
Ethical approval for this study was obtained from Malaysian Institute of Public Health, regis-
tration number NMRR-13-93-15292 and from the University of Malaya Ethical Committee.
Permission to conduct the study was also obtained from the State Health Director, District
Heath Offices and the respective Medical Officers.
Self-care. Diabetes self-care was assessed using the Malay version of the Summary of Dia-
betes Self Care Activities scale. The Malay version of the Summary of Diabetes Self Care Activi-
ties scale has 12 items and measures levels of diabetes self-care in 5 major areas; diet, exercise,
adherence to medication, blood glucose testing and foot care. Every item measures the number
of days each diabetes self-care activities were practiced in the last seven days, and is scored
between 0 to 7. To assess overall diabetes self-care, the score of all items was divided with the
total number of items. Similarly, to assess self-are for individual areas of diabetes care, the
score of all items within the respective area of diabetes care was divided with the correspond-
ing number of items. From a possible score of between 0 to 7, a score of 4 and above was con-
sidered as good practice [15, 16].
Self-efficacy. Self-efficacy was assessed using the Malay version of the Diabetes Manage-
ment Self Efficacy scale [15]. This questionnaire has 14 items and measures self-efficacy in 4
major areas; diet, exercise, medication adherence and blood glucose control. Each item was
scored between 0 to 10. The scoring of this scale was based on the total score of all items, with

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 Factors influencing diabetes self-care

higher score indicating better self-efficacy. There was no scoring for individual areas of self-
efficacy. The possible score for this scale was between 0 to 140.
Depression. Depression was assessed using the Malay version of the PHQ (Patient
Health Questionnaire) 9 item questionnaire. The Patient Health Questionnaire-9 (PHQ-9)
is a self-report measure to screen for depression, consisting of nine questions with each item
being scored from 0 to 3. The PHQ-9 is scored by calculating the total score of all 9 items.
The total PHQ-9 scores ranges from 0 to 27 with the scores of 10 or more categorized as
depression [17].
Diabetes distress. Diabetes distress was assessed using the Diabetes Distress Scale (DDS),
a 17 item questionnaire, measuring 4 domains of distress; [18] emotional burden, physician
related distress, regimen related distress and interpersonal distress. Each item was measured
on a Likert Scale of 16, where higher values indicate distress. The DDS allows overall distress
or the individual domain to be measured. The score for the scale was based on the average
score of all the items, with a possible score of between 1 to 6. A score of 3 or more was catego-
rized as distress. This questionnaire was not available in the Malay language. Originally in the
English language, it was translated and validated in this study

Data collection tools and measurements

The consented eligible patients were required to complete the survey. A face-to-face interview
was conducted. Self reported data regarding socio-demographics, diabetes self-care practices,
self-efficacy, depression and diabetes distress were collected by trained interviewers.

Translation, pre-test and pilot test

Originally in English and not available in the Malay language, the Diabetes Distress Scale was
translated and validated prior being used. The scale has 17 items, measuring distress in four
domains; emotional burden, physician related distress, regiment related distress and interper-
sonal distress. As the scale was not available in the Malay language, it underwent a translation
process. The forward translation was performed by 3 individuals while the backwards transla-
tion by 2 individuals. All translators were familiar and fluent with the original language and
target language. A panel decided on the best translation that suited the target population. The
translated version underwent pre-testing involving 16 patients with diabetes and pilot testing
involving 40 patients with diabetes recruited from the same study setting. All the domains had
good internal consistency with Cronbach Alpha >0.7.

Results
Four hundred and eighty eligible patients were approached, 391 agreed to participate in this
study, giving a response rate of 81.5%. The sex, age, duration of diabetes and HbAc1 values
were comparable between responder and non-responder (Refer Table 1)
After data cleaning, only 371 participants were included for analysis. The mean age of the
participants was 55.33 10.09 years. Among the 371 study participants, 141 (38.0%) were
males, 215(58.0%) were of Malay ethnicity followed by Indians at 110 (29.6%) and Chinese at
46 (12.4%).
Majority of the study participants, n = 189 (50.9%) attained primary education (6 years of
formal education), followed by secondary education (711 years of formal education), n = 149
(40.2%) and lastly tertiary education (12 years of formal education) n = 33 (8.9%). The most
prescribed oral hypoglycemic agent was biguanide, n = 340 (91.6%), followed by sulphonyurea,
n = 251 (67.7%), acarbose n = 18 (4.9%) and lastly glitazones, n = 9 (2.4%). One hundred and
three (27.8%) study participants were prescribed insulin injections. Among the study

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 Factors influencing diabetes self-care

Table 1. Comparison of baseline characteristics between responder and non-responder.

Variables Mean SD pvalue
Responder (391) NonResponder (89)
Sex* Male(145) Male(40) 0.169
Female(246) Female(49)
Age (years) 55.33 10.09 55.71 12.63 0.762
Duration of diabetes (years) 6.02 4.60 5.26 4.04 0.153
HbA1c (%) 8.77 2.29 8.50 1.96 0.308

t-test was performed for continuous data

* Chi-square performed with a significance level set at <0.05.

https://doi.org/10.1371/journal.pone.0175096.t001

participants, 41 (11.4%) had retinopathy, 21 (5.8%) had ischemic heart disease, 4 (1.1%) had
stroke while 2 (0.6%) had nephropathy.
The mean diabetes self-care score was 3.87 0.82, with 170 (45.8%%) categorized as prac-
ticing overall good diabetes self-care. For the individual self-care domains, medication adher-
ence had the highest score, followed by foot care, diet, exercise and lastly self-monitoring of
blood glucose, with the respective scores being 6.01 1.98, 5.63 1.84, 4.70 1.56, 2.77 1.78
and 1.38 1.59. Among the 371 study participants, 303 (81.7%) practiced good medication
adherence, 290 (78.2%) practiced good foot care, 266 (71.7%) practiced good diet, 112 (30.2%)
had good exercise practices and lastly 32 (8.6%) had good self-monitoring of blood glucose
practices.
The mean depression score was 4.58 2.57, with 16(4.3%) categorized as depressed. The
mean diabetes distress score was 1.54 0.66, with 20 (5.4%) categorized as distressed. The
mean self-efficacy score was 104.08 23.20, from a possible score of between 0 to 140. (Refer
Table 2)
The self-care practices were similar regardless of sex, age, ethnicity, education level, diabetes
complications and diabetes medication. Similarly, depression was not influenced by sex, age,
ethnicity, education level, diabetes complication or diabetes medication. Self-efficacy level was
significantly higher among those with secondary education level when compared to those with
primary education level. Self-efficacy was similar between sex, age group, ethnicity, complica-
tion status and diabetes medication. Diabetes distress was significantly higher among the
Malays when compared to the Indians and among those with tertiary education when com-
pared to those with primary education. Diabetes distress level was similar between sex, age
group, complication status and diabetes medication. (Refer Table 3).
To assess the relationship between self-care with self-efficacy, depression and diabetes dis-
tress as illustrated in Fig 1, a partial least square structural equation modeling analysis was per-
formed using the SmartPLS 3 software. As indicated in Fig 2, there was a significant direct
positive effect from self-efficacy (path coefficient = 0.438, p<0.001) to diabetes self-care. There
were also significant direct negative effects from depression (path coefficient = -0.263,
p<0.001) and from diabetes distress (path coefficient = -0.230, p<0.001) to diabetes self-effi-
cacy. There was a significant positive effect from diabetes distress (path coefficient = 0.268,
p<0.001) to depression. Both depression and diabetes distress had no significant direct associ-
ation with self-care, but had significant negative indirect effect on self-care, via self-efficacy.
The indirect effect of depression (path coefficient = -0.115, p<0.001) and distress (path coeffi-
cient = -0.122, p<0.001) indicate that depressed and distressed individuals had lower self-effi-
cacy and performed poorer self-care. This model explained 22% of variation in self-care.
(Refer Table 4)

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 Factors influencing diabetes self-care

Table 2. Participants demographics, self-care and psychosocial factors.

Characteristics Mean SD N (%)
Age (years) 55.33 10.09
Sex
Male 141 (38.0%)
Female 230 (62.0%)
Race
Malay 215(58.0%)
Chinese 46 (12.4%)
Indian 110 (29.6%)
Education level
Primary education (16 yrs) 189 (50.9%)
Secondary education (711 yrs) 149 (40.2%)
Tertiary education (12 yrs) 33 (8.9%)
Medication type
Biguanide 340 (91.6%)
Sulphonyurea 251 (67.7%)
Acarbose 18 (4.9%)
Glitazone 9 (2.4%)
Insulin 103 (27.8%)
Complications of diabetes
Ischemic Heart Disease 21 (5.8%)
Stroke 4 (1.1%)
Nephropathy 2 (0.6%)
Retinopathy 41 (11.4%)
SDSCA score (self-care) 3.87 0.82
Good practice 170 (45.8%)
Poor practice 201 (54.2%)
Diet score 4.70 1.56
Good practice 266 (71.7%)
Poor practice 105 (28.3%)
Exercise score 2.77 1.78
Good practice 112 (30.2%)
Poor practice 259 (69.8%)
Medication adherence score 6.01 1.84
Good practice 303 (81.7%)
Poor practice 68 (18.3%)
SMBG score 1.38 1.59
Good practice 32 (8.6%)
Poor practice 339 (91.4%)
Foot care score 5.63 1.98
Good practice 290 (78.2%)
Poor practice 81 (21.8%)
PHQ score (depression) 4.58 2.57
Depressed 16(4.3%)
Non-Depressed 355 (95.7%)
DDS score (distress) 1.54 0.66
Distressed 20 (5.4%)
Non-Distressed 350 (94.6%)
DMSE score (self-efficacy) 104.08 23.20
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 Factors influencing diabetes self-care

Table 3. Socio-demographic characteristics and its associated factors among the study participants.
Characteristics, n(%) Self-care Self-efficacy Diabetes distress Depression
Mean SD P value Mean SD P value Mean SD P value Mean SD P value
Sex 0.645
Male, 141(38.0%) 3.79 0.77 0.181 104.51 21.34 0.777 1.62 0.71 0.066 4.50 2.54
Female, 230(62.0%) 3.91 0.70 103.81 24.30 1.49 0.62 4.63 2.60
Ethnicity 0.681
Malay, 215(58.0%) 3.82 0.90 0.392 103.86 25.29 0.535 1.63 0.72 0.007b 4.67 2.85
Chinese, 46(12.4%) 3.92 0.67 101.21 21.69 1.46 0.67 4.35 2.16
Indian, 110(29.6%) 3.94 0.68 105.70 19.22 1.39 0.47 4.50 2.12
Age 0.776
60 years, 255(68.7%) 3.92 0.70 0.071 105.25 22.75 0.15 1.53 0.66 0.970 4.61 2.62
>60 years, 116(31.3%) 3.77 0.70 101.51 24.05 1.54 0.66 4.46 2.44
c
Education level 0.008 0.245
Primary, 189(50.9%) 3.78 0.74 0.080 101.46 23.53 0.012a 1.49 0.62 4.74 2.70
Secondary, 149(40.2%) 3.98 0.85 108.05 21.09 1.53 0.65 4.32 2.29
Tertiary, 33(8.9%) 3.90 1.00 101.18 28.06 1.88 0.84 4.91 2.98
Complication status 0.913 0.425 0.286 1.00
With at least one complication, 67(18.1%) 3.86 0.78 102.03 23.31 1.63 0.77 4.58 2.79
No complication, 304(81.9%) 3.87 0.82 104.53 23.18 1.52 0.64 4.58 2.52
Diabetes treatment 0.056 0.929 0.071 0.491
OHA only, 268(72.2%) 3.81 0.81 104.32 23.27 1.52 0.62 4.60 2.47
Insulin only, 18(4.9%) 4.21 0.85 104.50 20.95 1.89 0.94 3.89 2.76
OHA and Insulin, 85(22.9%) 3.97 0.82 103.23 23.64 1.54 0.71 4.67 2.83
a
secondary educationprimary education = 6.59
b
MalaysIndians = 0.231
c
tertiary educationprimary education = 0.384

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Fig 2. Relationship between depression, diabetes distress and self efficacy with self-care practices.
**p<0.001.
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 Factors influencing diabetes self-care

Table 4. Direct and indirect effects.

Outcome Direct effect Indirect effect Total effect
Self care
Self-efficacy !self-care 0.438** 0.438
Depression ! self-care 0.036 -0.115** -0.079
Distress ! self-care -0.109 -0.122** -0.231
Self-efficacy
Depression ! self-efficacy -0.263** -0.263**
Distress ! self-efficacy -0.230** -0.070* -0.300**
Depression
Distress ! depression 0.268** 0.268*

*p<0.01,
**p<0.001

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The response to the 17 items of diabetes distress scale was subjected to principal axis factor-
ing to test the dimensionality of the items in the construct [19]. Items which had poor conver-
gence (correlation <0.3) with the construct or poor discriminance (correlation >0.9) were
removed. Items with poor factor loading (<0.5) were also removed. In the final version of the
questionnaire, the emotional burden domain had 4 items (item number 4 removed due to
poor correlation), the physician related distress domain had 3 items (item number 9 removed
due to poor factor loading), the regimen related distress domain had 4 items (item number 14
removed due to poor factor loading) and the interpersonal domain had 3 items. The sample
size was adequate with as the KMO values were >0.6, and had good convergence validity as
the AVE were around or more than 50% (Refer Table 5). All pairwise correlations between the
constructs were less than 0.85. Hence, there is sufficient discriminant validity between the con-
struct (Refer Table 6).

Discussion
As has been shown from the pilot study and the factor analysis, the translated Diabetes distress
Scale was valid. Factor analysis was performed to ensure that the translated Diabetes distress
Scale measures what it was meant to while enabling the items to be reduced into a smaller set to
save time and facilitate easier interpretation [20]. The final translated Diabetes Distress scale has
14 items. All the items within the respective domains had item correlation of between 0.30.9,
which meant that all the items measured the same underlying theory. The KMO (Kaiser-
Meyer-Olkin) value for all domains of the translated Diabetes Distress scale were > 0.6, indicat-
ing that the sample size was sufficient to perform a factor analysis. Only one factor was extracted
from each domain, with the factor loading of all items being >0.5, indicating good relationship
between each item with the underlying factor[20]. All pairwise correlations between the con-
structs were less than 0.85, indicating that there was no sign of multicollinearity [21].
The baseline characteristics between responder and non-responder were the same, thus
reducing any possible responder bias.
Though there is limited information regarding diabetes self-care practices among Malay-
sians, the finding of this study was in agreement with the available studies which reported non
satisfactory diabetes self-care practices [13, 22]. Medication adherence was the most practiced
self-care and this was most likely because medication was provided for free by the healthcare
provider and unlike diet and exercise which requires lifestyle changes, it was easier to performed
[23]. Furthermore, the immediate effect or derangement of health outcome if medication

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 Factors influencing diabetes self-care

Table 5. Factor analysis of the diabetes distress scale.

Items Factor loading
Emotional Physician Regimen Inter -personal
burden related distress related distress
distress
1. Feeling that diabetes is taking up too much of my mental and physical energy every
day.
2. Feeling angry, scared, and/or depressed when I think about living with diabetes. 0.769
3. Feeling that diabetes controls my life. 0.634
a
4. Feeling that I will end up with serious long-term complications, no matter what I 0.524
do.
5. Feeling overwhelmed by the demands of living with diabetes. 0.749
6. Feeling that my doctor doesnt know enough about diabetes and diabetes care. 0.796
7. Feeling that my doctor doesnt give me clear enough directions on how to manage 0.722
my diabetes.
8. Feeling that my doctor doesnt take my concerns seriously enough. 0.723
b
9. Feeling that I dont have a doctor who I can see regularly enough about my 0.488
diabetes.
10. Feeling that I am not testing my blood sugars frequently enough. 0.728
11. Feeling that I am often failing with my diabetes routine. 0.802
12. Not feeling confident in my day-to-day ability to manage diabetes. 0.654
c
13. Feeling that I am not sticking closely enough to a good meal plan. 0.469
14. Not feeling motivated to keep up my diabetes self-management. 0.771
15. Feeling that friends or family are not supportive enough of self-care efforts (e.g. 0.657
planning activities that conflict with my schedule, encouraging me to eat the "wrong"
foods).
16. Feeling that friends or family dont appreciate how difficult living with diabetes can 0.794
be.
17. Feeling that friends or family dont give me the emotional support that I would like. 0.816
Correlation matrix 0.3250.587 0.5270.571 0.4050.708 0.5200.648
KMO (Kaiser-Meyer-Olkin) value 0.741 0.705 0.742 0.696
AVE (Average variance extracted) 48% 56% 55% 58%
Initial items 5 4 5 3
Final items 4 3 4 3
a
removed (correlation = 0.272)
b,c
removed (Factor loading <0.5)

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prescription was not followed may increase their compliance rate [24]. Unlike medications
which were provided for free, glucose testing machines and their test strips were not provided
by the health clinics and patients were required to purchase it themselves. Having to personally
finance the cost for self-monitoring of blood glucose may limit the practice [22, 25].

Table 6. Correlation between domains of the translated diabetes distress scale.

Correlation between constructs
Construct Emotional Physician Regimen Interpersonal
Emotional -
Physician 0.619 -
Regimen 0.793 0.692 -
Interpersonal 0.677 0.617 0.816 -
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 Factors influencing diabetes self-care

In this study, sex did not influence self-care. Reports regarding the association between sex
with self-care has not been consistent [26, 27], and is influenced by the local and traditional
sociocultural gender role [28]. The self-efficacy levels were similar between sex in this study.
Adebayo et al. [29] and Venkataraman et al. [30] reported that when controlled for social gen-
der role and sociodemographic factors, self-efficacy does not differ between sex. This study
found no association between sex with diabetes distress or depression. Previous studies have
reported that females were more likely to experience diabetes distress and depression [4, 31,
32] and this has been attributed to their biological nature, difference in mood and gender roles
[33, 34].
This study found no association between age with self-care, and similar findings have been
reported by other studies [3538]. Age was not associated with self-efficacy, depression and
diabetes distress in this study. This finding was in agreement with previous studies which
reported that age was not associated with psychosocial factors, but instead other factors such
as sociodemographic level, social support, comorbidity and overall well-being were [3942].
The self-care practices, self-efficacy and depression were similar between ethnicities. Diabe-
tes distress was lowest among the ethnic minority. This finding did not conform to previous
finding reported elsewhere. Though there is no specific information regarding Malaysian dia-
betics, study elsewhere have associated ethnic minorities as marginalized groups with issues
concerning access to healthcare services [43]. Ethnic minorities have also been reported to face
more socioeconomic constraints, poor education and perceived discrimination, thereby
increasing the levels of depression and diabetes distress [4, 44]. In this study, all the partici-
pants regardless of ethnicity or socioeconomic status had equal access to healthcare services.
The education level did not influence diabetes self-care practices. Previous studies reported
that those with higher education performed better self-care as they had better awareness [45].
In this study, all, the participants had equal access to healthcare services. Self-efficacy was
higher among those with higher education. This finding was in agreement with previous stud-
ies [46, 47]. This study found higher levels of diabetes distress among those with tertiary educa-
tion. The association between education level with diabetes distress has not been consistent as
other factors such as employment and income which are closely related to education influ-
ences distress as well [48, 49].
In this study, diabetes complications were not associated with diabetes self-care, self-effi-
cacy, distress or depression. Previous studies have reported that patients with diabetes
experiencing more or severe complications were associated with poorer self-care, lower self-
efficacy, depression and diabetes distress [31, 50]. In this study, the severity of the complica-
tions were not explored, which may have influenced the current finding.
This study found that the type of medication prescribed did not influence diabetes self-care,
self-efficacy, diabetes distress or depression. Other studies have reported that those on insulin
exercised lesser due to the fear of hypoglycemia [51] and were more likely to be non-compliant
to insulin injections as it causes discomfort and interferes with their daily activities [52]. The
complexity of insulin therapy has been reported to result in poorer self-efficacy [53] especially
concerning the proper timing and dosages, while the discomfort and interference of daily
activities associated with insulin injections has been regarded as burdening by some, resulting
in significant emotional distress [54] and a higher prevalence of depression among insulin
users [54, 55].
Using partial least square to assess structural relationship, this study found that self-efficacy
was a strong predictor of diabetes self-care. The positive association between self-efficacy and
diabetes self-care practices was in agreement with previous studies [5658]. High levels of self-
efficacy is associated with better self-autonomy, more confidence, more initiative and persis-
tence in dealing with daily needs of diabetes care [59]. A higher level of self-efficacy also

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 Factors influencing diabetes self-care

ensures the continuity of appropriate diabetes self-care practices [60]. A high sense of self-effi-
cacy amplifies and strengthens an individuals well-being in many ways. Individuals with con-
fidence in their capabilities looks at difficult tasks as challenges to be overcome rather than a
problem to be avoided [61].
Contrary to what we expected, in this study, depression did not influence self-care practices.
This finding could have been due to the low prevalence of depression and difference in study
population [62]. Furthermore, the almost free health services among the participants of this
study could have served as a protective factor from depression [63]. Similarly, in this study,
diabetes distress did not influence self-care practices. This finding could have been due to the
low prevalence of distress among the study participants and the sociocultural background of
the participants. Previous studies have reported that socio-cultural norms influences ones per-
ception of disease. Studies have shown that Asians and Caucasians perceive disease differently
[64]. Though not having any direct association with self-care, both depression and diabetes
distress were indirectly associated with self-care via self-efficacy. Diabetics experiencing
depression and distress had lower levels of self-efficacy and later practiced poorer self-care.
Diabetics experiencing distress have been reported to have lower levels of self-efficacy [65],
while depression leads to problems such as apathy, hopelessness, fatigue, memory problems
and loss of confidence in performing daily activities which are all required in managing a
chronic disease like diabetes [66, 67].
The positive association between distress with depression was in agreement with previous
studies [68, 69]. Diabetes distress is caused by the difficulty in coping with diabetes in daily
life. A minimal amount of diabetes distress is part of living with diabetes. However, when
severe enough, or exacerbated by other environmental or personal factor, diabetes distress
maybe severe enough to lead to depression [68].
Overall, among the study population, self-efficacy was the most important factor in deter-
mining good diabetes self-care. Though depression and diabetes distress affected self-care
indirectly via self-efficacy, the prevalence of these conditions were low. Thus, to improve self-
care practices, effort must be focused on enhancing self-efficacy levels, while not forgetting to
deal with depression and diabetes distress, especially among those with poor self-efficacy.

Conclusion
This study is the first in our knowledge to explore the relationship between depression, diabe-
tes distress and self-efficacy with self-care practices among Malaysians with type 2 diabetes.
Having higher levels of self-efficacy was associated with better diabetes self-care practices. Fur-
thermore, managing depression and diabetes distress is important among diabetics as it may
lead to poor self-efficacy and subsequently poorer diabetes self-care. Based on the insights
gained from this study, future research should focus on the same topic, with more emphasis
on increasing patients self-efficacy level and to reduce depression and diabetes distress with
the ultimate aim of improving diabetes self-care practices.

Limitations
There are limitations to this study that should be acknowledged. Firstly, the result of this study
represents the population under study, which are people with type 2 diabetes who were being
cared for in government healthcare centers in the district of Hulu Selangor. Therefore, the
results should not be generalized and needs to be replicated in different patient groups. Sec-
ondly, the questionnaires utilized in this study were self-reported. Thirdly, this study was of a
cross sectional study design, thus no statement of causality can be made.

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 Factors influencing diabetes self-care

Supporting information
S1 File. Raw data file.
(XLSX)

Acknowledgments
The authors would like to thank the doctors and nurses working in health clinics in the District
of Hulu Selangor for their help and hospitality.

Author Contributions
Conceptualization: CD.
Data curation: CD.
Formal analysis: KC.
Funding acquisition: CD.
Investigation: CD KC.
Methodology: KC.
Project administration: CD.
Resources: CD.
Software: KC.
Supervision: CD.
Validation: KC.
Visualization: CD KC.
Writing original draft: CD.
Writing review & editing: CD KC.

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