Skip to main content
Download PDF
Download ePub

Illness perceptions, self-care practices, and glycemic control among type 2 diabetes patients in Chiang Mai, Thailand

Archives of Public Health volume 80, Article number: 134 (2022) Cite this article

Abstract

Background

Diabetes Self-Management Education (DSME) is a fundamental aspect of diabetes care, but no standard program exists in Thailand. Understanding current patterns of illness perceptions (concerns) and self-management practices among patients with diabetes in Thailand is vital to develop culturally tailored DSME programs. This study sought to explore the association between reported self-management practices and diabetes perceptions on glycemic control among patients with type 2 diabetes in Chiang Mai Province, Thailand. Specifically, the study examined whether the association between illness perceptions and diabetes control was mediated by self-management.

Methods

This was a cross-sectional study conducted among type 2 diabetes patients on outpatient care and follow-up in four districts hospitals in Chiang Mai, Thailand. Illness perceptions was measured by the Brief Illness Perceptions Questionnaire (BIPQ). Self-management practices were measured by Summary Diabetes Self-Care activities (SDSCA). For illness perceptions and self-management practices, patients were classified into two groups, high level and low level based on the median values. Univariate and multivariable analyses were done to determine the association between the determinant factors: self-care practices and illness perceptions and the outcome of interest- good glycemic control (HbA1c < 7%).

Results

Of the 200 participants recruited into the study, 180 completed the questionnaire. Only 35% of participants had good glycemic control (HBA1c < 7.0). Both illness perceptions and self-management practices were independently linked to glycemic control. Among illness perceptions, a sense of personal control was strongly associated with good glycemic control (p = 0.01). For self-management, appropriate diet (p = 0.03) and medication adherence (p = 0.05) were associated with good glycemic control. After adjustments for key baseline characteristics, patients with high levels of illness perceptions were less likely to achieve glycemic control (OR 0.55, 95% CI 0.29 to 1.14, p = 0.11) and those with high level of self-management were more likely to achieve glycemic control (OR 2.11, 95% CI 1.04 to 4.30, p = 0.04). The effect size for illness perception attenuated when further adjusted for levels of self-management (OR 0.88, 95% CI 0.39 to 1.96, p = 0.75) while the effect size for self-management and glycemic control did not materially change (OR 2.30, 95% CI 1.06 to 5.02, p = 0.04).

Conclusion

Illness perceptions and self-management practices are associated with glycemic control. Future culturally tailored interventions in Thailand aimed at improving glycemic should focus on personal control, improving diet and treatment adherence as these are more likely to help improve diabetes control as demonstrated in this study.

Peer Review reports

Background

The global burden of diabetes is increasing and is one of the major causes of morbidity and mortality [1, 2]. Thailand has undergone rapid epidemiological, demographic, and nutrition transitions leading to an increasing prevalence of diet-related, non-communicable diseases, such as diabetes [3,4,5]. The prevalence of type 2 diabetes in Thailand has increased from 2.3% in 1991 to about 8.5% in 2017 and over 4.2 million cases [6]. This growing diet-related non-communicable disease (NCD) burden warrants ways to help improve in the diagnosis, treatment, and management of diabetes.

In diabetes management, great emphasis has been placed on self-management practices—the day-to-day activities patients carry out that promote their health. Diabetic patients are purported to spend only 1% of their time with a healthcare professional. This means that the bulk of management and care for this lifelong disease falls upon patients and their caregivers [7]. Hence, empowering patients with the necessary knowledge and skills to better manage their chronic conditions is key in diabetes care [8].

Significant evidence shows that self-management is effective in improving outcomes such as glycemic control, quality of life, all-cause mortality risk, body mass index and blood pressure [9,10,11,12,13,14]. Despite having a strong universal health care system and recognizing the importance of self-management for diabetes, Thailand has yet to introduce a national diabetes self-management education program [15]. A study in rural Thailand showed improved self-efficacy and quality of life of a family-oriented, self-management program compared to routine care [16], but it is uncertain if these benefits would persist beyond the short-term [17, 18]. Other Low-and Middle- income countries settings cite cost of continuing education programs, human resource constraints, and logistical challenges as reasons limiting the implementation and long-term benefits of diabetes education programs [19]. These factors also constrain self-management education programs in Thailand [20], for although self-management features prominently in the Thai diabetes management guidelines [21], there are no mechanisms or structures through which healthcare providers can promote self-management for their patients [20].

In Thailand, behavioral change, and self-management education programs for people with diabetes are often offered in outpatient settings. Current efforts are underway to design and evaluate a scalable diabetes self-management education (DSME) program for primary care in Thailand [22, 23]. Not only will programmatic issues need to be addressed, but a successful, widespread diabetes self-management program in Thailand will also need to be guided by behavioral theories and tailored to the local context [24]. Behavioral theory can inform an approach to understanding how perceptions among Thai patients with diabetes influence their behaviors and potential adherence to DSME programs. Leventhal’s self-regulatory model [25]—a well-researched approach—considers an individuals’ cognitive and emotional perceptions as they relate to illness in three stages: (1) forming a representation of the illness; (2) adopting coping behaviors, and (3) appraising the efficacy of these behaviors [25, 26]. Thus suggesting that a patient’s illness perceptions can directly relate to their self-management behaviors [27, 28]. While there is some evidence to suggest that aspects of illness perceptions are associated with medication adherence and attendance rate among patients with diabetes in Thailand [29, 30], very little is known about the illness perceptions and current self-care practices and among diabetic patients in Thailand. Moreover, illness perceptions and self-care practices can also vary between different settings [31, 32].

A better understanding of illness perceptions and their relation to appropriate diabetes self-management practices will provide a stronger, conceptual grounding for development of diabetes self-management education programs in Thailand. This study, therefore, sought to explore the association between reported self-management practices and diabetes perceptions on glycemic control among patients with type 2 diabetes in Chiang Mai Province, Thailand. Specifically, the study examined whether the association between illness perceptions and diabetes control was mediated by self-management.

Methods

Study setting, recruitment, and design

This quantitative cross-sectional study was conducted among type 2 diabetes patients in four districts hospitals within Chiang Mai province, Thailand between March, and August 2019. Study participants were selected from those diagnosed with diabetes and on out-patient care and follow-up at any of these four district hospitals. Nurses helped sequentially identify eligible patients and consent was obtained by researcher assistants who had no role in management of the patients. Eligible patients from each site were identified until target recruitment, 50 participants from each site, was reached. Only participants with hemoglobin A1C (HbA1c) tests done in the 6 months prior to the survey were recruited. This was to ensure that glycemic control represented by this HBA1c was reflective of current self-management practices being assessed. Patients that were < 18 years old and those severely ill or cognitively impaired were excluded.

Data collection, tools and definitions

Self-administered questionnaires were used for data collection with the help of clinical research assistants who were trained before data collection started. Data collected included socio-demographic characteristics (age, gender, occupation, religion), place of routine follow-up, education level, health insurance scheme, average income, illness perception and self-management practices. Clinical data included height and weight, duration with diabetes, insulin therapy and presence of comorbidities.

Illness perceptions

The Brief-illness perceptions Questionnaire (BIPQ) is a validated tool used to assess illness perceptions among patients with chronic conditions such as diabetes [26]. It has been shown to have good psychometric properties including validity and reliability in over 36 countries [33], including Thailand. The Thai version has been used to explore perceptions among people with hypertension and demonstrated good test–retest reliabilities between 0.75 to 0.97 for each of the eight domains of illness perceptions [34]. The original term “illnesses” used in the questionnaire was replaced with “diabetes” for the purposes of this study. The eight domains of illness perception and questions used to assess were:

  1. 1)

    Consequences: How much does your diabetes affect your life?

  2. 2)

    Timeline: How long do you think your diabetes will continue?

  3. 3)

    Personal control: How much control do you feel you have over your diabetes?

  4. 4)

    Treatment control: How much do you think your treatment can help your diabetes?

  5. 5)

    Identity: How much do you experience symptoms from your diabetes?

  6. 6)

    Concern: How concerned are you about your diabetes?

  7. 7)

    Coherence: How well do you feel you understand your diabetes?

  8. 8)

    Emotional: How much does your diabetes affect you emotionally?

Each BIPQ domain is scored from 0–10, ranging from 0 meaning ‘not at all’ and 10 representing extreme effects upon an individuals’ life, and a spectrum of responses in between. Scores from all 8 questions were summed up after reversing for item 3, 4, and 7 to give an overall score ranging from 0 to 80. BIPQ tool primarily measures negative illness perceptions as indicated by the questions. However, question 3,4 and 7 assess positive illness perceptions hence the need for reversal of scores in these questions in the cumulative score. A high score shows that the participant feels threatened by their diabetes condition. The level of illness for this study was classified into two groups with “high” and “low” illness perception falling above or below the median, respectively. A “high” illness perception indicates a high level of negative perceptions which suggest that the patient may not be coping well with diabetes. Conversely, a “low” illness perception indicates low negative perceptions which suggests that the patients may be coping well with diabetes.

Diabetes self-management

The Summary Diabetes Self-Care Activities Questionnaire SDSCA [35] was specifically developed to provide more robust measures of self-care practices in a codified manner and has been translated into Thai [36]. The tool is broken down into fifteen questions covering five major aspects of self-management: diet (5 questions), physical activity (2 questions), blood sugar testing (2 questions), medication use (1 question), and foot care (5 questions). Participants were asked how many days in the past seven days did they engaged in appropriate self-care activities related to each of the five major aspects. The overall score was obtained by adding the mean scores for diet, physical activity, blood glucose testing, foot care and medication resulting in a range of scores between 0(lowest) and 35(highest). Participants were categorized as “high” meaning good self-care practices or “low” meaning poor self-care practices using the median cut-off.

Diabetes control

The latest HBA1C of the participants was obtained from participants’ medical history. HBA1C was considered as a continuous variable and as a categorical variable with < 7% considered good control and poor control (≥ 7.0%) [37, 38].

Data analysis

Descriptive statistics were summarized as means and standard deviation (SD) for normally distributed continuous variables or median and interquartile ranges (IQR) for variables with non-normal distributions [39]. Univariate analysis was done for all the domains of self-management practices and illness perception with glycemic control using chi-square, t-test or Wilcoxon Rank Sum test as appropriate.

As outlined in the introduction, based on a patient’s illness perception they might adopt appropriate coping strategies and behaviors which should then lead to better glycemic control. A mediation analysis was performed using an approach described by Baron and Kenny [40, 41] to examine whether the association between illness perception and glycemic control was mediated by appropriate self-management practices in the population. We examined the following steps as part of the mediation analysis:

  1. 1)

    Whether there’s an association between illness perception self and glycemic control

  2. 2)

    Whether there’s an association between self-management and glycemic control

  3. 3)

    Whether there’s an association between illness perception and self-management practices

  4. 4)

    Whether the association between illness perception and glycemic control attenuated when self-management (the mediator) was included in the model

  5. 5)

    Whether the association between self-management and glycemic control remain consistent when illness perception was included in the model (not mediated or not confounded by illness perception)

Final multivariable logistic regression models were adjustment for significant baseline socio-demographic and clinical characteristics in univariate analyses.

Results

Socio-demographic and clinical characteristics

Two hundred participants were recruited into the study. Of these 180 completed the questionnaire. The mean age of the participants was 63.1(sd 9.0) years, two-thirds (67.1%) of whom were female. Only 35% of the participants had good glycemic control (HBA1c < 7.0%), 40% of participants had BMI higher than 25 which is categorized as obese according to the Asian Pacific BMI chart [42]. The median duration with diabetes was 10.3 (sd 7.7) years. Majority of the participants had primary school level of education (76.7%). Of these baseline and clinical characteristics, gender (female) (p = 0.03) advancing age (p < 0.01), longer duration with diabetes (p = 0.05) and being on insulin therapy (p < 0.01) showed a statistically significant association with poor glycemic control (Table 1).

Table 1 Socio-demographic and clinical characteristics
Full size table

Illness perceptions and glycemic control

Of the individual domains, the highest median score (10/10) was for “timeline”, indicating that most patients believed that their condition was likely to be permanent rather than temporary. Other concerns were related to the consequences of diabetes in their life (“consequences”) with a median score of 5/10 followed by concerns regarding their ability to control their diabetes with a median score of 4/10 (“concern”). The overall mean score for illness perceptions was 29.4 out of 80 (sd 11.6). Higher level of illness perception was statistically significantly associated with poor glycemic control (p = 0.03). Those with poor glycemic control had a mean illness score of 31.0 (sd 11.6) while those with good glycemic control had a mean illness score of 26.5 (sd 11.2) Of all illness perception domains, personal control was strongly associated with glycemic control (p = 0.01) (Table 2).

Table 2 Illness perception and diabetes control
Full size table

Self-management practices and glycemic control

Some aspects of self-management, specifically, foot care and medication adherence were practiced daily. The scores were lower for glucose monitoring, diet and physical activity with median scores of 0 (IQR 0 to 0), 2.8 (IQR 0 to 7) and 3.0 (IQR 1.4 to 4.2) respectively. Overall, higher levels of self-management practices were associated with good glycemic control (p = 0.04). Among the specific aspects of self-management, increasing self-care in terms of diet (p = 0.03) and medication adherence (p = 0.05) were significantly associated with good glycemic control (Table 3).

Table 3 Self-care activities and diabetes control
Full size table

Multivariable analyses and mediation analyses

Participants with low levels of illness perception had slightly higher levels of self-management (median 20.6, IQR 17.4 to 23.4) compared to those with high levels of illness perception (median 19.4, IQR 16.0 to 22.0) but this did not achieve statistical significance (Fig. 1).

Fig. 1
figure 1

Self-care activity scores by levels of illness perception

Full size image

After adjustments for key baseline characteristics, there was some weak evidence to suggest that illness perception was associated with glycemic control. Those with high levels of illness perceptions were less likely to achieve glycemic control (OR 0.55, 95% CI 0.29 to 1.14, p = 0.11). The association between self-management and glycemic control was stronger. Those with a high level of self-management were more likely to achieve glycemic control (OR 2.11, 95% CI 1.04 to 4.30, p = 0.04) (Table 4 Model 1).

Table 4 Self-care activity, illness perception and diabetes control
Full size table

For the mediation analyses, the effect size for illness perception attenuated when further adjusted for levels of self-management practices (OR 0.88, 95% CI 0.39 to 1.96, p = 0.75) while the effect size for self-management and glycemic control did not materially change (OR 2.30, 95% CI 1.06 to 5.02, p = 0.04) (Table 4 Model 2).

Discussion

This study explored the association between illness perceptions, self-management practices, and glycemic control among patients with type 2 diabetes in northern Thailand. The most concerning illness perceptions among patients were the aspects related to timeline (diabetes likely to be permanent rather than temporary), consequences (diabetes is affecting my life), and personal control (no control over my diabetes). Higher illness perception scores were associated with poor glycemic control. Low self-management practices, particularly for diet and glucose testing, were also associated with poor glycemic control. The study also demonstrated that the association between illness perception was mediated by self-management practices.

In the current study, just over a third of the participants met the recommended HBA1c cut-off of 7.0%. It is consistent with findings in other studies, where more than 60% of patients often do not hit the recommended glycemic target [43]. This study suggests that higher patients’ illness perceptions about diabetes was associated with poorer glycemic control. One domain in particular, personal control—belief in one’s own ability to control their diabetes—was strongly linked with glycemic control. This finding is supported by previous studies where personal control was the strongest predictor of glycemic control [44, 45], including in the original studies validating the use of the BIPQ [26]. However, in contrast to what was reported in the Broadbent et al. study [26], we did not find an association between glycemic control and the treatment control or identity domains, potentially due to the differences in the study populations. In the study by Broadbent et al., conducted in New Zealand, the mean treatment control illness score was 8.0 while it our study, it was only 2.68. The mean identity illness score was also higher in the Broadbent study compared to our study (4.6 vs 2.7). This reflects that many cultural and socioenvironmental aspects may affect the patient’s illness perceptions, which may include level of education and literacy among the population and how health care is organized and delivered [46]. This finding helps to narrow down the illness perception domains that require specific focus and emphasis in addressing among patients with T2DM in Thailand.

For self-management practices, it is noteworthy that glucose monitoring was not routinely done as this is not covered in the universal health coverage scheme and would therefore be an additional cost to the patient [15]. While this study found good treatment adherence and footcare, there was poor adherence to healthy diet and physical activity. The current study corroborates findings elsewhere in Thailand where only 31% of participants adhered to appropriate diet and exercise regimens [47]. Our current study noted that diet and adherence to medications were the self-management practices most strongly associated with glycemic control and adds to a growing literature that suggests that sub-optimal individual level self-management and structural health systems challenges persist in Thailand [15].

In theory, patients who were less threatened by diabetes (illness perception) would be expected to perform better self-management activities, and consequently, have improved glycemic control [29, 41, 44]. While the results in this study generally supported this statement, there was insufficient evidence for an association between illness perceptions and self-management practices. However, it was difficult to discern the overall framework as the study also demonstrated some evidence that the relationship between illness perception and glycemic control was mediated through self-management practices.

Another important finding from this study is the significant association between patients characteristics including age, gender, duration with diabetes, and glycemic control. Several previous studies have observed that glycemic control is worse in females than age-matched males [48,49,50]. We also demonstrated that glycemic control is worse in younger patients < 60yrs compared to older patients. These findings have been demonstrated in other studies [51].Our study also showed that glycemic control worsens with increasing number of years with diabetes which has been shown in other studies [52]. These reflect potential risk groups where illness perceptions should be explored.

This current study demonstrates the significant role of self-care practices in influencing diabetes outcomes and the need to focus on changing patients’ perceptions about their illnesses. These findings give credence to current efforts to roll out a structured education program tailored to the Thai population with the aim of empowering patients to take charge of their illnesses. This may help improve diabetes control in Thailand which has stagnated within the 33–36% range from 2012–2018 [53, 54].

The findings of this current study should be interpreted carefully in light of some limitations. First, the questionnaire for assessing self-management practices only collects data about the past seven days and assumes that this is representative of the patient’s daily practice. Although a limitation, the reliability and validity of the SDSCA has been demonstrated in published literature and in other developing Asian countries. In addition, we acknowledge that level of education may lead to more awareness about these self-care behaviours and could result in recall bias. However, the level of education did not significantly differ between those with good control and poor control thus unlikely to cause differential misclassification in reporting of self-care activities. Most of our patients were between 60 and 70 years old and we excluded those with severely impaired cognition, thus our results may not be generalizable to the full spectrum of patients living with diabetes. We used Leventhal’s self-regulatory model as the basis for our analyses. However, there are other behavioral theories, such as social cognitive theory or the theory of planned behavior [55] that could also explain some of the pathways between how illness perceptions, self-management behaviors and glycemic control. However, data on motivation, beliefs, and intention were not available to explore these theories in detailed [56].

Conclusions

The study describe key illness concerns and area of self-management which could be improved among diabetes patients on outpatient care and follow-up in Thailand. It also provides evidence to support the need to address these illness concerns as a way to promote self-management practices. Particular emphasis should be placed on personal control, improving patient diet, physical activity and treatment adherence. Diabetes self-management programs in Thailand may consider such information in future to help in the development of culturally tailored interventions.

Availability of data and materials

The dataset used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

BIPQ:

Brief illness perceptions questionnaire

DSME:

Diabetes Self-Management Education

HbA1c:

Hemoglobin A1C

IQR:

Interquartile range

NCD:

Non-communicable disease

SD:

Standard deviation

SDSCA:

The summary diabetes self-care activities questionnaire

References

  1. Lancet T. The diabetes pandemic. Lancet. 2011;378(9786):99.

    Article  Google Scholar 

  2. Hu F, Satija A, Manson J. Curbing the diabetes pandemic: the need for global policy solutions. JAMA. 2015;313(23):2319–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Bundhamcharoen K, Odton P, Phulkerd S, Tangcharoensathien V. Burden of disease in Thailand: changes in health gap between 1999 and 2004. BMC Public Health. 2011;11(1):53.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Patcharanarumol W, Panichkriangkrai W, Wangmo S, Thammatacharee J, Uechi M, Wanwong Y. Diabetes prevention and care in the universal health coverage context: the example of Thailand. WHO South-East Asia J Public Health. 2016;5(1):27–33.

    Article  PubMed  Google Scholar 

  5. Angkurawaranon C, Jiraporncharoen W, Chenthanakij B, Doyle P, Nitsch D. Urbanization and non-communicable disease in Southeast Asia: a review of current evidence. Public Health. 2014;128(10):886–95.

    Article  CAS  PubMed  Google Scholar 

  6. Papier K, Jordan S, D‘Este C, Bain C, Peungson J, Banwell C, et al. Incidence and risk factors for type 2 diabetes mellitus in transitional Thailand: results from the Thai cohort study. BMJ Open. 2016;6(12):e014102.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Hinder S, Greenhalgh T. “This does my head in”. Ethnographic study of self-management by people with diabetes. BMC Health Serv Res. 2012;12(1):83.

  8. Ratner N, Davis E, Lhotka L, Wille S, Walls M. Patient-centered care, diabetes empowerment, and type 2 diabetes medication adherence among American Indian patients. Clin Diabetes. 2017;35(5):281–5.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Tachanivate P, Phraewphiphat R, Tanasanitkul H, Jinnawaso R, Areevut C, Rattanasila R, et al. Effectiveness of diabetes self – management education in thais with type 2 diabetes. Pacific Rim Int J Nurs Res. 2019;23(1):74–86.

    Google Scholar 

  10. Keeratiyutawong P, Hanucharurnkul S, Melkus G, Panpakdee O, Vorapongsathorn T. Effectiveness of a self-management program for Thais with type 2 diabetes. Thai J Nurs Res. 2006;10:85–97.

    Google Scholar 

  11. Wattana C, Srisuphan W, Pothiban L, Upchurch S. Effects of a diabetes self-management program on glycemic control, coronary heart disease risk, and quality of life among Thai patients with type 2 diabetes. Nurs Health Sci. 2007;9(2):135–41.

    Article  PubMed  Google Scholar 

  12. Captieux M, Pearce G, Parke H, Epiphaniou E, Wild S, Taylor S, et al. Supported self-management for people with type 2 diabetes: a meta-review of quantitative systematic reviews. BMJ Open. 2018;8(12):e024262.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Chrvala C, Sherr D, Lipman R. Diabetes self-management education for adults with type 2 diabetes mellitus: a systematic review of the effect on glycemic control. Patient Educ Couns. 2016;99(6):926–43.

    Article  PubMed  Google Scholar 

  14. He X, Li J, Wang B, Yao Q, Li L, Song R, et al. Diabetes self-management education reduces risk of all-cause mortality in type 2 diabetes patients: a systematic review and meta-analysis. Endocrine. 2017;55(3):712–31.

    Article  CAS  PubMed  Google Scholar 

  15. Yan LD, Hanvoravongchai P, Aekplakorn W, Chariyalertsak S, Kessomboon P, Assanangkornchai S, et al. Universal coverage but unmet need: NATIONAL and regional estimates of attrition across the diabetes care continuum in Thailand. PLoS One. 2020;15(1):e0226286.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wichit N, Mnatzaganian G, Courtney M, Schulz P, Johnson M. Randomized controlled trial of a family-oriented self-management program to improve self-efficacy, glycemic control and quality of life among Thai individuals with type 2 diabetes. Diabetes Res Clin Pract. 2017;123:37–48.

    Article  PubMed  Google Scholar 

  17. Miller C, Gutschall M, Holloman C. Self-monitoring predicts change in fiber intake and weight loss in adults with diabetes following an intervention regarding the glycemic index. Patient Educ Couns. 2009;76(2):213–9.

    Article  PubMed  Google Scholar 

  18. Johnjumrut C. Individualized empowerment approach in dietary self-management of improve metabolic control in patients with type 2 diabetes. Nakhon Pathom: Mahidol University; 2007.

  19. Powers M, Bardsley J, Cypress M, Duker P, Funnell M, Fischl A, et al. Diabetes self-management education and support in type 2 diabetes: a joint position statement of the American diabetes association, the American association of diabetes educators, and the academy of nutrition and dietetics. Clin Diabetes. 2016;34(2):70–80.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Preechasuk L, Sriussadaporn P, Likitmaskul S. The obstacles to diabetes self-management education and support from healthcare professionals’ perspectives: a nationwide survey. Diabetes Metab Syndr Obes. 2019;12:717–27.

  21. The Royal College of Physicians of Thailand. Clinical Practice Guideline for Diabetes 2017. Pathum Thani: ROMYEN MEDIA COMPANY LIMITED; 2017.

  22. Angkurawaranon C, Papachristou Nadal I, Mallinson PAC, Pinyopornpanish K, Quansri O, Rerkasem K, et al. Scalable solution for delivery of diabetes self-management education in Thailand (DSME-T): a cluster randomised trial study protocol. BMJ Open. 2020;10(10):e036963.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Papachristou Nadal I, Aramrat C, Jiraporncharoen W, Pinyopornpanish K, Wiwatkunupakarn N, Quansri O, et al. Process evaluation protocol of a cluster randomised trial for a scalable solution for delivery of Diabetes Self-Management Education in Thailand (DSME-T). BMJ Open. 2021;11(12):e056141.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new medical research council guidance. BMJ. 2008;337:a1655.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Leventhal H, Nerenz D, Steele D. Illness representations and coping with health threats. 1st ed. London: Routledge; 1984.

    Google Scholar 

  26. Broadbent E, Petrie K, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res. 2006;60(6):631–7.

    Article  PubMed  Google Scholar 

  27. Petrie K, Weinman J. Patients’ perceptions of their illness: the dynamo of volition in health care. Curr Dir Psychol Sci. 2012;21(1):60–5.

    Article  Google Scholar 

  28. Petrie K, Weinman J. Perceptions of health and illness: current research and applications. 1st ed. Amsterdam: Psychology Press; 1997.

  29. Jiraporncharoen W, Pinyopornpanish K, Junjom K, Dejkriengkraikul N, Wisetborisut A, Papachristou I, et al. Exploring perceptions, attitudes and beliefs of Thai patients with type 2 diabetes mellitus as they relate to medication adherence at an out-patient primary care clinic in Chiang Mai, Thailand. BMC Fam Pract. 2020;21(1):173.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Thongsai S. Do illness perceptions predict the attendance rate at diabetic outpatient clinic? Global J Health Sci. 2014;7(2):254–62.

    Article  Google Scholar 

  31. Sowattanangoon N, Kotchabhakdi N, Petrie KJ. The influence of Thai culture on diabetes perceptions and management. Diabetes Res Clin Pract. 2009;84(3):245–51.

    Article  PubMed  Google Scholar 

  32. Chamroonsawasdi K, Chottanapund S, Tunyasitthisundhorn P, Phokaewsuksa N, Ruksujarit T, Phasuksathaporn P. Development and validation of a questionnaire to assess knowledge, threat and coping appraisal, and intention to practice healthy behaviors related to non-communicable diseases in the Thai population. Behav Sci. 2017;7(2):20.

    Article  PubMed Central  Google Scholar 

  33. Broadbent E, Wilkes C, Koschwanez H, Weinman J, Norton S, Petrie KJ. A systematic review and meta-analysis of the brief illness perception questionnaire. Psychol Health. 2015;30(11):1361–85.

    Article  PubMed  Google Scholar 

  34. Leelacharas S, Kerdonfag P, Chontichalalalauk J, Sanongdej W. Illness perceptions, lifestyle behaviors, social support, and cardiovascular risks in people with hypertension in urban and rural areas of Thailand. Pacific Rim Int J Nurs Res. 2015;19(3):245–56.

    Google Scholar 

  35. Toobert D, Hampson S, Glasgow R. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care. 2000;23(7):943–50.

    Article  CAS  PubMed  Google Scholar 

  36. Keeratiyutawong P, Hanucharurnkl S, Melkus G, Vorapongsathon O. Effectiveness of a self-management program for Thais with type 2 diabetes: an integrative review. Thai J Nurs Res. 2006;10(2):85–97.

    Google Scholar 

  37. American Diabetes Association. Glycemic targets: standards of medical care in diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S55-64.

    Article  Google Scholar 

  38. Ebe K, Bando H, Yamamoto K, Bando M, Yonei Y. Daily carbohydrate intake correlates with HbA1c in low carbohydrate diet (LCD). J Diabetology. 2017;1(1):4–9.

    Google Scholar 

  39. Whitley E, Ball J. Statistics review 1: presenting and summarising data. Critical Care (London, England). 2002;6(1):66–71.

    Article  Google Scholar 

  40. Baron R, Kenny D. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–82.

    Article  CAS  PubMed  Google Scholar 

  41. Kenny D. MEDIATION [Internet]. 2018 [updated September 25, 2018; cited 2019 Jul 8]. Available from: http://davidakenny.net/cm/mediate.htm.

  42. World Health Organization. Regional Office for the Western Pacific. The Asia-Pacific perspective: redefining obesity and its treatment. Sydney: Health Communications Australia; 2000.

    Google Scholar 

  43. Del Prato S, Felton A, Munro N, Nesto R, Zimmet P, Zinman B. Improving glucose management: ten steps to get more patients with type 2 diabetes to glycaemic goal. Int J Clin Pract. 2005;59(11):1345–55.

    Article  PubMed  Google Scholar 

  44. Kugbey N, Oppong Asante K, Adulai K. Illness perception, diabetes knowledge and self-care practices among type-2 diabetes patients: a cross-sectional study. BMC Res Notes. 2017;10(1):381.

    Article  PubMed  PubMed Central  Google Scholar 

  45. McSharry J, Moss-Morris R, Kendrick T. Illness perceptions and glycaemic control in diabetes: a systematic review with meta-analysis. Diabet Med. 2011;28(11):1300–10.

    Article  CAS  Google Scholar 

  46. Petrie KJ, Jago LA, Devcich DA. The role of illness perceptions in patients with medical conditions. Current Opinion in Psychiatry. 2007;20(2).

  47. Howteerakul N, Suwannapong N, Rittichu C, Rawdaree P. Adherence to regimens and glycemic control of patients with type 2 diabetes attending a tertiary hospital clinic. Asia Pac J Public Health. 2007;19(1):43–9.

    Article  CAS  PubMed  Google Scholar 

  48. Kautzky-Willer A, Kosi L, Lin J, Mihaljevic R. Gender-based differences in glycaemic control and hypoglycaemia prevalence in patients with type 2 diabetes: results from patient-level pooled data of six randomized controlled trials. Diabetes Obes Metab. 2015;17(6):533–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Choe S-A, Kim JY, Ro YS, Cho S-I. Women are less likely than men to achieve optimal glycemic control after 1 year of treatment: A multi-level analysis of a Korean primary care cohort. PLoS ONE. 2018;13(5):e0196719.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Duarte F G, da Silva Moreira S, Almeida MdCC, de SouzaTeles CA, Andrade CS, Reingold AL, et al. Sex differences and correlates of poor glycaemic control in type 2 diabetes: a cross-sectional study in Brazil and Venezuela. BMJ Open. 2019;9(3):e023401.

    Article  Google Scholar 

  51. Nanayakkara N, Ranasinha S, Gadowski AM, Davis WA, Flack JR, Wischer N, et al. Age-related differences in glycaemic control, cardiovascular disease risk factors and treatment in patients with type 2 diabetes: a cross-sectional study from the Australian national diabetes audit. BMJ Open. 2018;8(8):e020677.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Mamo Y, Bekele F, Nigussie T, Zewudie A. Determinants of poor glycemic control among adult patients with type 2 diabetes mellitus in Jimma University Medical Center, Jimma zone, south west Ethiopia: a case control study. BMC Endocr Disord. 2019;19(1):91.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Sakboonyarat B, Pima W, Chokbumrungsuk C, Pimpak T, Khunsri S, Ukritchon S, et al. National trends in the prevalence of glycemic control among patients with type 2 diabetes receiving continuous care in Thailand from 2011 to 2018. Sci Rep. 2021;11(1):14260.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Sakboonyarat B, Rangsin R, Kantiwong A, Mungthin M. Prevalence and associated factors of uncontrolled hypertension among hypertensive patients: a nation-wide survey in Thailand. BMC Res Notes. 2019;12(1):380.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Hood K, Hilliard M, Piatt G, Levers-Landis C. Effective strategies for encouraging behavior change in people with diabetes. Diabetes management. 2015;5(6):499–510.

    Article  CAS  PubMed  Google Scholar 

  56. Jiraniramai S, Jiraporncharoen W, Pinyopornpanish K, Jakkaew N, Wongpakaran T, Angkurawaranon C. Functional beliefs and risk minimizing beliefs among Thai healthcare workers in Maharaj Nakorn Chiang Mai hospital: its association with intention to quit tobacco and alcohol. Subst Abuse TreatPrev Policy. 2017;12(1):34.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study is supported by UK Medical Research Council (MRC) grant number (MR/R020876/1) and the Thailand Research Fund (TRF) grant number (DBG6180007). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Nuffield Department of Surgical Sciences, Medical Sciences Division, University of Oxford, Oxford, UK

    Elisha Ngetich

  2. Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand

    Chanapat Pateekhum, Ahmar Hashmi, Kanokporn Pinyopornpanish & Chaisiri Angkurawaranon

  3. Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK

    Iliatha Papachristou Nadal & Sanjay Kinra

  4. Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Iliatha Papachristou Nadal

  5. Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK

    Mike English

  6. ASEAN Institute for Health Development, Mahidol University, Salaya, Nakorn Pathom, Thailand

    Orawan Quansri

  7. Suratthani Rajabhat University, Surat Thani, Thailand

    Nutchanart Wichit

Authors
  1. Elisha Ngetich
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chanapat Pateekhum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ahmar Hashmi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Iliatha Papachristou Nadal
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kanokporn Pinyopornpanish
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mike English
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Orawan Quansri
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Nutchanart Wichit
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Sanjay Kinra
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Chaisiri Angkurawaranon
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NP, OQ, KP, SJ and CA conceived and designed the study; CP,AH, NW, CA were involved in the acquisition of data; EN, CP, ME and CA were involved in the analyses; EN, CP, AH, and CA were involved in the initial draft; IPN, KP, ME, OQ,NW and SK critically revised the manuscript. All authors approved the submission and agreed to be accountable for the work.

Corresponding author

Correspondence to Chaisiri Angkurawaranon.

Ethics declarations

Ethics approval and consent to participants

Ethical approval for the study was sought and granted by Chiang Mai University (No. 326/2018) and London School of Hygiene and Tropical Medicine (16113/RR/12850) before the study was conducted. Written informed consent was obtained from all eligible participants before the start of the study.

Consent for publication

Not applicable.

Competing of interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ngetich, E., Pateekhum, C., Hashmi, A. et al. Illness perceptions, self-care practices, and glycemic control among type 2 diabetes patients in Chiang Mai, Thailand. Arch Public Health 80, 134 (2022). https://doi.org/10.1186/s13690-022-00888-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13690-022-00888-1

Keywords

Archives of Public Health

ISSN: 2049-3258