Patients living with diabetes are primarily managed and supported by nurses in primary health care (PHC). Therefore, PHC nurses require knowledge of diabetes and confidence (self-efficacy) to perform diabetes self-management support (SMS).
This study evaluated the diabetes knowledge, self-efficacy and performance of diabetes SMS by PHC nurses.
Primary health care facilities in King Sabata Dalindyebo subdistrict, O.R. Tambo district, Eastern Cape.
A quantitative cross-sectional and simple correlational design was used. Registered nurses (
Participants’ diabetes knowledge mean scores were high (mean of 11.9, standard deviation [s.d.] 1.8, out of 14). Self-efficacy scores (mean 18.91, s.d. 3.2 out of 24) were higher than performance of SMS scores (mean 17.81, s.d. 3.3 out of 24). Knowledge was not associated with self-efficacy or performance, but self-efficacy was positively correlated with performance of SMS (
Diabetes knowledge of PHC nurses in this study does not translate into self-efficacy and the performance of SMS in practice, indicating the need for specific SMS training, support by experienced mentors, appropriate guidelines and comprehensive integrated chronic care systems.
This is the first study to report on the SMS self-efficacy and performance of PHC nurses in South Africa.
The increasing mortality rate of people living with diabetes is a global concern. According to the International Diabetes Federation, South Africa ranks amongst the top five countries with the highest diabetes incidence in Africa, with an age-adjusted (20–79 years) comparative incidence of 10.8%.
The rise in noncommunicable chronic diseases (NCDs) such as diabetes compelled countries like South Africa to introduce an integrated chronic disease model (ICDM) for primary health care (PHC).
Self-management is an ongoing process where individuals are actively involved on a daily basis in the management of their chronic condition.
Studies conducted in sub-Saharan Africa show that self-management is generally poor and a serious threat to the health of individuals living with diabetes.
Currently, there is no structured self-management programme in South Africa. Although the ICDM has a component called ‘assisted self-management’, which is primarily provided by ward-based PHC outreach teams, there are no specific guidelines for nurses or other healthcare workers on how to provide SMS.
A quantitative cross-sectional and simple correlational design was used to investigate the associations between nurses’ diabetes knowledge and SMS self-efficacy and performance of SMS. The study was conducted in PHC clinics and community health centres (CHCs) in King Sabata Dalindyebo (KSD) subdistrict in the O.R. Tambo District, Eastern Cape. King Sabata Dalindyebo was selected as it is the largest subdistrict in O.R. Tambo District with 49 clinics and five CHCs.
Professional nurses rendering PHC services in 17 KSD clinics were the study’s target population (
The first author and a fieldworker collected data between July and August 2021. Since data were collected in PHC facilities, COVID-19 regulations were followed.
The self-administered questionnaire comprised three sections: (1) demographic questions; (2) the Diabetes Basic Knowledge Test (DBKT) adapted from the modified version of the ‘Diabetes Knowledge Test’,
The original DBKT contained 52 multiple-choice questions coded as 0 = incorrect, 1 = I don’t know and 2 = correct. In order to reduce the questionnaire length and contextualise the instrument, the items were reduced to 14 items that focused on type 1 and 2 diabetes mellitus aetiology, management of the disease and effects of insulin, including physiological action and storage. Two local experts reviewed the adapted instrument to assess relevancy, alignment with local guidelines and contextual appropriateness. A knowledge score was created by adding the number of correct responses (total out of 14).
The SEPSS is a validated instrument containing 36 items in six subscales (Assess, Advise, Agree, Assist, Arrange and Partnership) that measures SMS self-efficacy and performance separately on a four-point Likert scale. Scoring of the SEPSS instrument required that participants rate both self-efficacy and performance on the same set of items. Scores range from 0 to 4 for the subscales and from 0 to 24 at a total scale. Higher scores on the SEPSS reflect a higher level of self-efficacy and performance of SMS.
The questionnaire was pilot tested with 16 PHC nurses who attended a diabetes management workshop to evaluate the readability and clarity of the questions and test the data collection procedures. Data were not included in the main study.
Reliability of the data collection instruments.
Instrument | Cronbach’s alpha | ICC (test–retest) | Present study Cronbach’s alpha |
---|---|---|---|
DBKT | 0.75 | - | 0.39 |
SEPSS – Self-efficacy | 0.96 | 0.95 | 0.89 |
SEPSS – Performance of SMS | 0.95 | 0.94 | 0.93 |
ICC, intraclass correlation coefficient; DBKT, Diabetes Basic Knowledge Test; SEPSS, Self-efficacy and Performance in Self-Management Support; SMS, self-management support.
Collected data were entered in the Statistical Package for the Social Sciences (SPSS) version 27 (IBM Corporation, Armonk, New York, United States) and analysed. For descriptive statistics, data were summarised; continuous variables such as age, knowledge and self-efficacy scores were reported by the mean, mode and median, depending on whether they were normally distributed or not. For data that were normally distributed, the mean and standard deviation (s.d.) were reported. Frequencies and percentages were calculated based on the number of valid responses (with missing values excluded).
To test for associations between the dependent continuous variables and independent variables with two categories, the Mann–Whitney
Ethical approval to conduct the study was received from the Health Research Ethics Committee (HREC) at Stellenbosch University (reference number S20/12/349), the Eastern Cape Department of Health (reference number EC_20204_003) and the O.R. Tambo District Health Department. Participants were given a choice of whether to participate or not, and they were informed that they were allowed to withdraw from the study at any point. All participants signed written consent forms. Data were collected anonymously and are being kept in a password-protected folder for five years.
The youngest participant was 24 and the eldest 61 years old (mean 42.3; s.d. 10.7) (not shown on table).
The demographic data of the participants measured on a nominal or ordinal level are displayed in
Demographic data.
Variable | Frequency | % |
---|---|---|
Female | 86 | 86.0 |
Male | 13 | 13.0 |
Nonbinary | 1 | 1.0 |
Professional nurse | 94 | 94.9 |
Senior professional nurse | 5 | 5.1 |
Diploma in Nursing | 58 | 59.2 |
B Cur | 24 | 24.5 |
Postgraduate | 16 | 16.3 |
Yes | 10 | 10.2 |
No | 88 | 89.8 |
Less than 1 month ago | 54 | 55.1 |
Less than 3 months ago | 11 | 11.2 |
3–6 months ago | 5 | 5.1 |
More than 6 months ago | 28 | 28.6 |
1–10 | 57 | 62.0 |
11–20 | 26 | 28.2 |
21–30 | 9 | 9.8 |
PHC, primary health care; B Cur, Baccalaureus Curationis (Bachelor’s Degree).
The youngest participant was 24 and the eldest 61 years old (mean 42.3; s.d. 10.7) (not shown on table).
The results of the knowledge questions are displayed in
Frequency of correct knowledge responses.
Variable | Correct response frequency | % |
---|---|---|
Aetiology | 82 | 82.0 |
Tests to monitor diabetes control | 87 | 87.0 |
Signs of hyperglycaemia | 83 | 83.0 |
Cause of hyperglycaemia | 45 | 45.0 |
When do you check for ketones? | 83 | 83.0 |
Signs of hypoglycaemia | 83 | 83.0 |
Cause of hypoglycaemia | 90 | 90.0 |
Insulin storage | 79 | 79.0 |
Normal fasting blood glucose level | 95 | 95.0 |
What guides your initial actions if a diabetic person is found unresponsive? | 96 | 96.0 |
Physiological actions of insulin | 78 | 78.0 |
Action to take if needle is contaminated | 77 | 77.0 |
What effect does insulin have on blood glucose? | 89 | 89.0 |
The most appropriate statements about management of type 2 diabetes | 82 | 82.0 |
The mean item responses to the items in the SEPSS instrument are indicated in
Self-efficacy and performance of self-management mean scores.
Variable | Self-efficacy |
Performance |
|||
---|---|---|---|---|---|
Mean | s.d. | Mean | s.d. | ||
Ask the patient what he or she thinks about living with diabetes in the future | 100 | 3.0 | 1.0 | 3.2 | 0.8 |
Ask what patient knows | 100 | 3.3 | 0.8 | 2.3 | 1.2 |
Ask a patient to share his emotions about diabetes | 100 | 2.7 | 1.1 | 2.7 | 1.1 |
Ask about available motivation and discipline to integrate diabetes in his life | 100 | 2.9 | 1.0 | 2.8 | 1.1 |
Ask how much confidence he has in his own abilities | 100 | 3.0 | 1.0 | 3.2 | 1.0 |
Ask what he can and wants to do for himself in his daily care related to diabetes | 100 | 3.4 | 0.7 | 3.2 | 0.9 |
Total | 3.06 | 0.7 | 2.81 | 0.8 | |
Ask patient what information he needs | 100 | 3.2 | 0.8 | 3.1 | 0.9 |
Ask the patient for permission to give information or advice | 100 | 3.2 | 0.9 | 3.0 | 0.9 |
Letting the patient restate information given | 100 | 3.2 | 0.8 | 3.0 | 0.9 |
Giving the patient education and instruction about the chronic condition | 100 | 3.4 | 0.8 | 3.6 | 0.7 |
Helping the patient to formulate questions to discuss with healthcare workers | 100 | 2.9 | 1.1 | 2.6 | 1.2 |
Involving the family when giving information and winstruction | 100 | 3.0 | 1.1 | 2.6 | 1.2 |
Total | 3.16 | 0.6 | 2.98 | 0.6 | |
Search for earlier positive experiences in achieving goals | 100 | 2.7 | 1.3 | 2.4 | 1.3 |
Let the patient prioritise when setting goals | 100 | 2.9 | 0.9 | 2.8 | 1.1 |
Developing a plan of action to achieve goals with patient | 100 | 3.0 | 1.0 | 2.9 | 1.0 |
Document the goals and agreements in patient record | 100 | 3.1 | 1.1 | 3.0 | 1.3 |
Help patient to make decisions concerning treatment | 100 | 3.3 | 1.0 | 3.3 | 0.8 |
Recognise patient uncertainty about making a treatment decision | 100 | 3.3 | 0.8 | 3.2 | 0.9 |
Total | 3.05 | 0.7 | 2.93 | 0.7 | |
Discuss with patient who he will inform about his chronic condition | 100 | 3.5 | 0.8 | 3.4 | 0.9 |
Encourage the patient to perform as many daily activities as possible | 100 | 3.5 | 0.6 | 3.5 | 0.7 |
Helping the patient to choose the activities that he can realistically do | 100 | 3.2 | 0.8 | 3.1 | 0.9 |
Discuss with the patient who can provide daily support | 100 | 3.2 | 1.0 | 3.0 | 1.0 |
Discuss with patient how he can make use of self-management assistive devices daily | 100 | 2.9 | 1.1 | 2.7 | 1.1 |
Assist patient to monitor his own health and physical reactions | 100 | 3.3 | 0.9 | 3.2 | 0.9 |
Total | 3.33 | 0.6 | 3.18 | 0.6 | |
Ask about convenient time for follow-up care | 100 | 3.4 | 0.8 | 3.2 | 1.5 |
Inform and coordinate with other health care professionals | 100 | 3.2 | 0.8 | 3.2 | 0.9 |
Using assistive devices and technology to provide remote guidance to the patient | 100 | 2.7 | 1.1 | 2.3 | 1.3 |
Facilitating the patient to easily stay in contact between appointments | 100 | 3.5 | 0.8 | 3.2 | 1.1 |
Initiating contact between appointments to discuss health and solve difficulties | 100 | 3.0 | 1.1 | 2.8 | 1.1 |
Examining progress of care plan actions together with the patient | 100 | 3.3 | 0.9 | 3.1 | 0.9 |
Total | 3.20 | 0.6 | 2.99 | 0.8 | |
Accepting patient experience as valuable information concerning care delivery | 100 | 3.0 | 0.9 | 3.0 | 1.1 |
Consider cultural background of the patient | 100 | 3.2 | 1.0 | 2.7 | 1.0 |
Determine together with patient how much of the care coordination I take for him | 100 | 3.0 | 0.9 | 2.4 | 1.3 |
Using the patient choices as the basis for care, even if it’s not ideal from a medical view | 100 | 2.6 | 1.3 | 3.1 | 1.1 |
Showing empathy when patient does not succeed in achieving the established goals | 100 | 3.2 | 1.0 | 3.2 | 0.9 |
Reflecting upon my own practice | 100 | 3.4 | 0.8 | 3.0 | 1.1 |
Total | 3.11 | 0.7 | 2.9 | 0.7 |
s.d. Standard deviation.
The subscale with the highest mean for self-efficacy and performance was ‘Assist’ with mean scores of 3.33 and 3.18, respectively.
The subscale with the lowest mean for self-efficacy was ‘Agree’ (mean 3.05), and for performance, it was ‘Assess’ (mean 2.93). Participants had lower self-efficacy in exploring previous positive experiences in achieving goals (mean 2.7) and were the least likely to ask what a person knows during the assessment (mean 2.3).
Participants further had low mean scores for both self-efficacy (mean 2.7) and performance (mean 2.3) for the item related to using assistive devices and technology to provide remote guidance to the patient.
The self-efficacy scale had a higher total mean (18.91, s.d. 3.2) than the performance scale (17.8, s.d. 3.3).
Participants’ diabetes knowledge mean scores were high, but there was no association between the knowledge score, the total self-efficacy and performance scores (
Correlations between knowledge, self-management support self-efficacy and performance.
Spearman’s rho | Knowledge score % performance | Total self-efficacy | Total |
---|---|---|---|
Correlation coefficient | 1.00 | −0.03 | −0.01 |
Sig. (2-tailed) | - | 0.07 | 0.03 |
100 | 100 | 100 | |
Correlation coefficient | 0.03 | 1.00 | 0.78 |
Sig. (2-tailed) | 0.75 | - | 0.00 |
100 | 100 | 100 | |
Correlation coefficient | −0.01 | 0.78 |
1.00 |
Sig. (2-tailed) | 0.32 | 0.00 | - |
100 | 100 | 100 |
, Correlation is significant at the 0.01 level (2-tailed).
Nurses with a PHC qualification had a significantly higher mean diabetes knowledge score (mean 92.9, s.d. 7.5) compared with those who did not have a PHC qualification (mean 83.8, s.d. 12.9) (Mann–Whitney
Primary health care nurses in this study had high diabetes knowledge scores, with a mean score of 11.9 out of 14 (85%), although only 64 participants had a knowledge score of ≥ 80%. The mean score is much higher compared with the mean score (54.5%) in a study conducted in Southern Carolina, which used the original DBKT tool.
Self-efficacy scores in this study were high (mean 18.91, s.d. 3.1) compared with a study conducted by Duprez et al. to validate the SEPSS tool in the Netherlands (mean 17.2, s.d. = 3.31).
Performance of SMS in this study was also higher (17.81, s.d. 3.3) compared with the study conducted by Duprez et al.
With the high burden of disease, the use of technology in diabetes self-management has become increasingly important.
The total mean performance in SMS score was slightly lower than the total self-efficacy score (17.81 vs. 18.91). Several factors may inhibit nurses from providing SMS, which include institutional factors and personal factors.
Inequities between public services and private services remain a challenge in South Africa.
Patients living with diabetes in PHC settings are primarily seen and managed by nurses. Community-based, nurse-led SMS interventions can improve the health-related outcomes of persons with diabetes if nurses are specifically trained.
We hypothesised that nurses’ diabetes knowledge would be positively associated with self-efficacy and the performance of diabetes SMS. Although knowledge was not associated with SMS self-efficacy or performance, SMS self-efficacy had a strong positive correlation with SMS performance. This means that nurses with self-efficacy may be more likely to perform SMS. The correlation found in the current study (
Years of experience as a professional nurse was correlated with SMS performance, although the correlation was weak (
To the best of our knowledge, this is the first study to assess diabetes SMS self-efficacy and performance in South Africa using previously validated tools. Limitations include convenience sampling and that some nurses were not available because of the COVID-19 pandemic and vaccination campaigns. To compensate, several attempts were made to include all available participants. The DBKT tool had questionable reliability even though it was validated by local experts and pilot tested. This may be because the participants did not have consistent levels of knowledge across the diabetes knowledge items and the number of items was reduced to shorten the questionnaire. The inherent limitation of self-report measures is subjectivity, and it may not reflect actual practice. This, however, further emphasises the need to educate nurses regarding the provision of SMS. The difference between the self-efficacy and performance of SMS scores reported in this study may not be of clinical significance. Data may not be generalisable outside the O.R. Tambo District.
Primary health care nurses in O.R. Tambo have high levels of diabetes knowledge; however, this does not translate into SMS self-efficacy and performance. Nurses need support to implement SMS through appropriate guidelines, education, training and mentoring, as well as comprehensive integrated chronic care systems.
The authors wish to acknowledge the primary care nurses who participated in this study. This article is partially based on Z.K. Landu’s thesis of the degree of Master of Nursing in the Faculty of Medicine and Health Sciences at Stellenbosch University with supervisor Dr T. Crowley, received April 2022.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Z.K.L. conducted the research and T.C. supervised the research process. Both Z.K.L. and T.C. contributed to writing the manuscript.
This research received no specific grant from any fundingagency in the public, commercial or not-for-profit sectors.
Data sharing does not apply to this article as no new data were created or analysed in this study.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.