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Determinants of healthful eating and physical activity among adolescents and young adults with type 1 diabetes in Qatar: A qualitative study

  • Hanan AlBurno ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Writing – original draft

    Affiliation Care and Public Health Research Institute (CAPHRI), Maastricht University, Netherlands, The Netherlands

  • Liesbeth Mercken,

    Roles Conceptualization, Formal analysis, Methodology, Supervision, Writing – review & editing

    Affiliations Care and Public Health Research Institute (CAPHRI), Maastricht University, Netherlands, The Netherlands, Faculty of Psychology, Department of Health Psychology, Open University of The Netherlands, Heerlen, The Netherlands

  • Hein de Vries,

    Roles Conceptualization, Methodology, Supervision, Validation, Writing – review & editing

    Affiliation Care and Public Health Research Institute (CAPHRI), Maastricht University, Netherlands, The Netherlands

  • Dabia Al Mohannadi,

    Roles Methodology, Resources

    Affiliation Department of Endocrinology and Diabetes, Hamad General Hospital, Doha, Qatar

  • Francine Schneider

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Supervision, Writing – review & editing

    Affiliation Care and Public Health Research Institute (CAPHRI), Maastricht University, Netherlands, The Netherlands



In Qatar, as in the rest of the world, the sharp rise in the prevalence of type 1 diabetes (T1D) is a leading cause for concern, in terms associated with morbidity, mortality, and increasing health costs. Besides adhering to medication, the outcome of diabetes management is also dependent on patient adherence to the variable self-care behaviors including healthful eating (HE) and physical activity (PA). Yet, dietary intake and PA in adolescents and young adults (AYAs) with T1D are known to fall short of recommended guidelines. The aim of this study was to develop an in-depth understanding of the behavioral determinants of HE and PA adherence among Arab AYAs within the age range of 17–24 years with T1D attending Hamad General Hospital.


Semi-structured, face-to-face individual interviews were conducted with 20 participants. Interviews were based on an integrative health behavior change model, the I-Change model (ICM). All interviews were audio-recorded, transcribed verbatim, and analyzed using the framework method.


More participants reported non-adherence than adherence. Several motivational determinants of adherence to HE and PA were identified. The majority of participants were cognizant of their own behaviors towards HE and PA. Yet, some did not link low adherence to HE and PA with increased risks of health problems resulting from T1D. Facilitators to adherence were identified as being convinced of the advantages of HE and PA, having support and high self-efficacy, a high level of intention, and a good health care system.


The suboptimal adherence in AYAs to HE and PA needs more attention. Supportive actions are needed to encourage adherence to a healthy lifestyle to achieve benefits in terms of glycemic control and overall health outcomes, with a special focus on adolescents. Interventions are needed to foster motivation by addressing the relevant determinants in order to promote adherence to these two behaviors in AYAs with T1D.


Type 1 diabetes (T1D) is the major type of diabetes in adolescents and young adults (AYAs) [1,2] accounting for more than 85% of all diabetes cases in AYAs under the age of 20 worldwide [1]. Globally, the prevalence of T1D in children and young adults has doubled since the nineteen nineties and is expected to double again in the coming few years [3] at an annual increment rate of 2–5% in many countries [4,5]. The Arab world has one of the highest global incidence and prevalence rates of T1D [68]. In Qatar, as in the rest of the world, the sharp rise in the prevalence of T1D is a leading cause for concern, in terms associated with morbidity, mortality, and increasing health costs [9,10]. AYAs with T1D are at an increased risk of developing diabetes-related complications including retinopathy, nephropathy, neuropathy, and cardiovascular disease at an early age [11,12].

T1D is a chronic disease that needs to be largely self-managed. Hence, the outcome of diabetes management is highly dependent on patient adherence to personal self-care behaviors, including healthful eating (HE) and physical activity (PA) [1315]. However, less attention has been given to adherence to lifestyle in T1D [16,17] than in type 2 diabetes (T2D) [17]. Non-adherence to HE and PA can contribute to poor glycemic control, increased risk of obesity, dyslipidemia, and cardiovascular disease (CVD) in T1D [1821]. Additionally, a mismatch between carbohydrate intake and insulin can result in hypo- and hyperglycemia, leading to short- and long-term complications [18]. Previous research supports the significance of HE adherence to diabetes outcomes [2224]. HE has been shown to improve blood glucose control [23] and contribute to weight management in people with T1D [24]. Regular PA, on the other hand, has been shown to reduce cardiovascular risk factors [25,26], decrease insulin resistance, have a beneficial effect on physical fitness [25] and long-term blood glucose control [27].

Given the importance of HE and PA for health outcomes for people living with diabetes, international guidelines promote its adherence in this population. The American Diabetes Association (ADA) guidelines recommend that “adolescents with T1D should be advised to perform at least 60 min per day of moderate- or vigorous-intensity aerobic activity, with strength training at least 3 days per week” [28,29]. Additionally, most young adults with T1D should be advised to perform at least 150 min/week of moderate-intensity aerobic PA (50–70% of maximum heart rate). Patients should also be encouraged to perform resistance exercise “at least two times per week on non-consecutive days” [29,30]. AYAs with T1D should also be encouraged to make improved food choices, limit consumption of fat-containing foods, added sugar and sodium, and consume sufficient amounts of whole-grain foods, vegetables, and fruits [18,31]. They also need to match insulin dose to carbohydrate intake. National and international guidelines call for dietetic advice on HE and carbohydrates counting techniques to be part of the routine diabetes review [29,32,33]. Further, the ADA recommends that all AYAs with T1D should limit energy consumption from saturated fat to less than 7% [34]. Research has highlighted the importance of individual dietary advice for people with T1D [35]. A higher level of dietetic input is certainly appropriate for people with living T1D on intensive insulin therapy regimes [36].

Despite these recommendations and known benefits of adherence, HE and PA in AYAs with T1D are known to fall short of recommended guidelines [15,18,23,37,38]. The published estimates of non-adherence rates to HE behaviors have ranged from 21% to 95% across studies [18]. It was found that adolescents with T1D were less active compared to their peers [37]. According to some studies, people living with diabetes have more difficulties adhering to a suitable diet and PA than to insulin medication [39,40]. These findings affirm the need for further investigations into adherence to HE and PA and their corresponding determinants in AYAs with T1D to better understand non-adherence and to guide developing interventions to increase adherence.

Several behavioral determinants have been found to affect patient adherence and, hence, metabolic control. These are related to various individual, social, and environmental variables [18,41]. At the individual level, research has identified knowledge, outcome expectations, emotional factors, self-efficacy, motivation, physical skills, and goal setting as important factors to self-care behaviors including HE and PA [4245]. At the social and environmental levels, communication with health care providers, and cultural, social, and family support were identified as important factors [46,47]. Still, suboptimal adherence and gaps in the literature exist. Additionally, many studies do not include all relevant determinants, hindering a comprehensive overview of its importance and decisions concerning what to focus on in interventions. Very few studies are available in Qatar and the rest of the Arab world that can be used to guide intervention development for AYAs. Consequently, this study employed an integrative model, the I-Change model (ICM) [4850] to facilitate a more comprehensive understanding of these two lifestyle behaviors and their corresponding determinants in people living with T1D. The ICM has been successfully used to predict and change lifestyle behaviors in people without diabetes [4953] and in people living with type 2 diabetes [54,55]. An essential feature of the ICM is that it acknowledges three phases in the process of behavior change: awareness, motivation, and action. These phases are particularly relevant for diabetes control as several patients are not optimally aware of non-adherence to the recommendations and do not plan or execute relevant actions to realize the prescribed recommendations. The ICM suggests that motivation factors (attitude, social influence beliefs, and self-efficacy) are influenced by different pre-motivational factors such as awareness factors (cognizance, knowledge, risk perceptions, and cues to action) and predisposing factors such as information factors (the quality of messages, channels, and sources used) [48,50]. Within the post-motivational phase, factors that increase the likelihood of intention being translated into action are action and coping planning [48]. Additionally, it is important to explore determinants within the dynamics of different family, social, and cultural environments. A greater understanding of health issues related to culture is critical because cultural beliefs and practices may facilitate or discourage diabetes management. In Qatar, factors related to HE and PA were reported in adults [5658] and adolescents from the general population [59], women with coronary disease [60], and in children with T1D [61]. Results showed the specific socio-cultural context of this region influences the decisions and behaviors to participate in a healthy lifestyle. However, evidence from AYAs with T1D is lacking. In this context, understanding the behaviors, their social-ecological and motivational determinants of individuals with T1D is vital to meet the complex demands of managing diabetes [62,63]. To the best of our knowledge, no research has studied this in Qatar. In sum then, the objectives of this study were, first, to identify the behaviors of AYAs with T1D towards HE and PA and, second, to examine the facilitating and hindering factors associated with these behaviors.


Research design

This study used a qualitative design by means of semi-structured, face-to-face individual interviews. Qualitative description design, frequently used in health behavior research, is recommended to describe as well as understand participants’ perspectives on a phenomenon [64,65]. This is essential to facilitate engaging diverse participants’ perspectives, integrating findings into the design and conduct of future research [66], and into more effective diabetes management programs and services aimed at minimizing barriers and maintaining/promoting facilitators towards HE and PA. Individual interviews were chosen to make allowances for cultural barriers on disclosing sensitive issues, but also to encourage open discussion in a free way without reservation or group factors, as research has shown that young people are often reserved about expressing themselves in front of other people [67]. The Institutional Review Board (IRB), Medical Research Centre Committee-Hamad Medical Corporation granted ethical approval. Research number 17017/17. Data was collected over a period of four months (October 2017 –January 2018).

Participants and recruitment

The target population of interest in this study consisted of AYAs living with T1D within the age range of 17–24 years, Qatari and non-Qatari (from countries in the Gulf Cooperation Council (GCC) and the Middle East and North Africa (MENA) region) living in Qatar, and who had been diagnosed with T1D for at least two months prior to the study. This was based on evidence from behavior psychology research which estimates the average time required for a new behavior to become automatic (assuming that the patients will start the new healthy behaviors at the time of their diagnosis, although some may be already engaged in HE and PA before their diagnosis) to be around 66 days [68]. The selection of an all-Arab sample was aimed at providing a genetically and/or culturally near-homogenous sample population to help eliminate extraneous factors that could act as potential confounders, such as socio-cultural factors like food habits. Patients with secondary diabetes that is a consequence of another medical condition or consumption of certain medications such as corticosteroids, and people with cognitive impairments, drug or alcohol dependence, or gestational diabetes were excluded.

In order to recruit AYAs, a purposive sampling method was used [69,70], i.e. physicians attending patients intentionally selected participants who met the predefined eligible criteria and referred them to the principal investigator (PI) (first author) for confirmation of eligibility. This sampling method was used to recruit patients with a diverse range of metabolic control (optimal, suboptimal, and poor), aiming to broaden the perspective on the topic. In adolescents, optimal metabolic control was defined as having HbA1c value <7.5% (<58mmol/mol), a poor metabolic control denoted an HbA1c >9% (>75mmol/mol), and suboptimal metabolic control was when the HbA1c value lay between 7.5–9% (58-75mmol/mol) [71]. In young adults, HbA1c levels were categorized into <7% (<53mmol/mol), 7–7.9% (53-63mmol/mol), and ≥8%(≥ 64mmol/mol), reflecting optimal, suboptimal, and poor metabolic control, respectively. This was based on the international HbA1c consensus committee recommendations [72] and clinical practice guidelines’ recommendations [7375]. At the beginning of each interview, the PI obtained the informed written consent forms from young adults aged 18 years or older and the written assent forms from those under 18 years old with their carers’ consents, using the procedure approved by the ethics committee. The forms included a sufficient explanation of the study.

Sample size

A total of 20 interviews was judged to be suitable for determining sample size adequacy to achieve data saturation based on similar previous research [76,77]. Additionally, we were guided by saturation parameters found in prior studies, i.e. focused research questions [78,79], mainly theory-driven themes [80], a relatively homogeneous sample, relatively long individual interviews, and the use of an intensive framework analysis strategy [81]. Further, we examined the depth and the richness of the collected information by using an analysis saturation grid during the analysis process [82].

Interview process and procedure

The first author (HB), trained in patients’ consultation and qualitative research, interviewed the participants using an interview guide. HB did not have a previous relationship with the participants. The interviews were conducted in a quiet area at the diabetes clinics in Hamad General Hospital, which is the major public hospital in Doha, Qatar, and were scheduled for approximately 60 minutes. Participants were assured that all data would be anonymized. At the beginning of each interview, the participants were familiarized with their diabetes care team and ADA recommendations for HE and PA [34,83] and were asked about demographics and clinical characteristics such as age, level of education, duration of diagnosis with diabetes, etc. All interviews were audio-recorded and transcribed verbatim.

Tool development

An open-ended interview guide was piloted and culturally adapted prior to its use. The guide was developed based on the socio-cognitive constructs in the ICM proposed by Vries [48] (Table 1). The guide was reviewed by an advisory group consisting of experts (e.g., those with knowledge and experience) in the areas of change theories, qualitative research, and T1D specialized health care providers (HCPs). Changes were made as appropriate, based on both a field test and expert opinion. The guide was aimed at enabling the interviewer to identify behavioral determinants while at the same time allowing some more exploration by using prompts and probes. The socio-demographic and medical background included information on gender, age, educational level, and diabetes and insulin history.

Data analysis

Demographic and clinical characteristics

Results of demographic and clinical characteristics data were expressed as mean [standard deviation (SD)] or percentage of total responses. Adherence and non-adherence were self-reported and assessed in the interview. At the beginning of the interviews, the participants were familiarized with their diabetes care team and ADA recommendations for HE and PA. Then, based on their answers during the interview, they were considered adherents; those respondents who reported that they always or most of the time follow the agreed recommendations from their diabetes care team for HE and PA; otherwise they were considered non-adherents. The percentages of patients with optimal, suboptimal, or poor metabolic control were determined as reflected by HbA1c, as an index of glycemic control over the previous 6–8 weeks. Data on HbA1c was collected from patients’ records, the purpose was to compare HbA1c results with participants’ perceptions of their level of control, and whether they perceive diabetes adherence to HE and PA would influence diabetes outcome.

Qualitative data analysis

The interviews were audio-recorded and transcribed verbatim in Arabic before being translated into English. For data management and analysis, the framework method was used, which involves a combination of inductive and deductive approaches [8487]. This method was deemed appropriate because of the need to both describe and interpret the diabetes self-management behavioral predictors. This method consisted of the following steps: (1) familiarization with the interview; during this step, the interviewer (first author) read the transcripts several times to produce an overall, general impression of the data; (2) coding; during this process, HB coded all transcripts by allocating text segments to multiple codes to account for the complexity of data and double-checked against the codes. FS and LM reviewed the codes to enhance the quality of the coding process [65,8890]. Then, codes and sub-codes were grouped to form main themes and categories. A codebook was developed using predefined themes from the interview guide; additional codes and sub-codes that emerged during data analysis were added to the initial codebook [91,92]; (3) developing the analytical thematic framework; a coding tree was created to form the working analytical framework; (4) indexing; applying the analytical framework, during which the thematic framework was applied to all transcripts and supplemented with new emerging themes and categories; (5) charting data into the framework matrix, where participants’ responses were summarized in a matrix for each health behavior; and (6) mapping and interpretation. To promote the reliability and validity of data during coding and analysis processes, thus rigor, data verification strategies were used [93]. This was achieved by (1) employing inductive and deductive methods, the researchers HB, LM, and FS regularly and iteratively discussed the coding system and analysis to validate the consistency in the application of codes, data interpretation, and formulation of findings [93,94]; (2) using a common conceptual framework with a priory defined codes, which were specific to particular interview questions [65,89]; (3) performing concurrent data collection and analysis to ensure methodological coherence; and (4) checking for sampling adequacy and saturation. Moreover, in order to maintain consistency with the study aim, we applied an “ad hoc unitization strategy” by including theoretically relevant simultaneous and interpretative codes in the coding frame and in the analysis and interpretation of data [65].


Demographic characteristics and medical status information

Out of the 20 interviewees, 55% were Qatari, and the distribution of males and females was equal. The mean age was 21.6 years (SD = 2.6). Demographic and medical status information are shown in Table 2.

Pre-motivational factors


Participants discussed topics related to their awareness of their behavior; awareness of risk perception of their own behavior; how these behaviors impacted their level of diabetes control; and awareness of the need to change their behaviors, if any. Participants who reported adherence to PA reported being adherent to HE [Quote #1], except for two cases where one patient was adherent to PA but not to HE, and vice versa [Quotes #2 and #3]. In relation to diet, the majority of participants indicated they were not following a dietary plan and that they were aware that they were non-adherent to HE; however, they did mention knowing how food affects their blood sugar levels. Some non-adherent respondents reported not being aware of the need to eat healthier; they remarked that they could eat whatever they wanted as long as they could adjust the insulin dose [Quote #4]. Similarly, many participants reported being aware that they were either inactive or non-adherent to the recommendations for performing PA. Some others indicated that they were already doing some kind of PA, which varied from walking during their working days to going to the gym. Several non-adherent participants realized that their poor HE habits and low level of PA had caused their diabetes to be uncontrolled [Quote #5]. Other reasons provided for poor and/or sub-optimal control were irregular sleep, carelessness, and overthinking.

Some respondents overestimated their level of diabetes control and were not fully cognizant of this. They considered themselves to have controlled diabetes, whereas actually, the results of their HbA1c indicated that they were either poorly controlled or had suboptimal control [Quote #6]. When participants were asked about the need to change their behaviors, if any, many non-adherent participants wished to increase activity levels and eat healthier. However, some of them indicated that they were not convinced of changing their behaviors regarding performing PA or HE because they failed to see a relation with diabetes control [Quote #7]. Other non-adherent participants indicated that their daily lifestyles were routines and habits that would be impossible to change [Quote #8].

Risk perception.

Most adherent participants and some non-adherent ones recognized the susceptibilities of getting diabetes complications as a result of non-adherence to HE and PA as recommended. They also acknowledged that the risks of complications could be severe. Other non-adherents felt differently and indicated that complications from diabetes would be beyond their control and would happen anyway regardless of what they did, as it is their fate. Some other non-adherents did not link risks of non-adherence to PA, in particular to diabetes complications [Quotes #9 and #10]. Some respondents felt that the complications would happen at an advanced age. A few non-adherent participants thought that the complications would be serious only if they did not administer insulin as recommended or if their HbA1c became high, and thus did not link increased severity of risks to low adherence. One participant did not recall the types of complications of diabetes [Quotes #11 and #12]. Relevant quotes and respondents relating to pre-motivational factors are found in Table 3.

Motivational factors


Irrespective of whether participants were adherents or not, many respondents indicated that HE and PA were linked to health benefits (both physical health and mental/psychological health) and more general advantages. For example, they discussed the advantages of HE and PA on their general diabetes control, such as achieving good glycemic control, and being able to decrease insulin doses [Quote #13]. Some others mentioned preventing, delaying, or avoiding complications as advantages of HE and PA. Some physical health benefits recognized were: losing or maintaining weight, improving body image, fitness, and overall health. In terms of psychological health advantages, respondents mostly mentioned enhancing their mood and living without worries. Additional general benefits for some interviewees were connected to health-related quality of life (HRQL), such as having a healthy life and the possibility of decreasing the chances of developing diseases. Participants also talked about general benefits relating specifically to performing PA [Quote #14]. Concerning healthy eating, the time needed to prepare and make healthy meals was mentioned as the main perceived practical disadvantage for non-adherents. Feeling deprived of their favorite food was the main psychological disadvantage for them. Participants who indicated that they were adherent to HE did not mention any disadvantages. Overall, adherent females reported having concerns about their weight and body image, which was a motivating factor to adhere to HE and PA for them.

Participants who performed PA regularly described physical disadvantages of performing PA, such as muscular pain, an increase in the risk of hypoglycemia and injuries. Non-adherent respondents also mentioned that fear of hypoglycemia (FoH) would hinder their adherence to PA. Time consumption was mentioned as the main practical disadvantage for non-adherents. Non-adherent participants also mentioned feelings of failure and low self-esteem resulting from their low adherence to PA in comparison with adherent patients [Quote #15].

Social influence.

Social influence was perceived by the respondents as either positive (prompting the behavior), negative (discouraging), or neutral (no support). The forms of positive social influence the adherents received were emotional and practical, such as exercising with them, cooking healthy food for them, reducing sugary intake, and stopping buying soft drinks [Quotes #16 and #17]. The majority of adherents showed that they mainly got their support from their families, then from professionals, and in a few cases, from observing other adherents. Few participants who did not follow healthy diets or perform regular PA admitted that they would sometimes accept the support and encouragement if given from close friends but not from their families. A few even said that they would listen to the advice about HE and performing PA, but would not follow it [Quote #18].

Friends were mentioned as having a greater negative influence on non-adherent respondents than families and co-workers. Friends mainly encouraged negative behavior, such as encouraging them to either eat sugary and unhealthy foods with them when hanging out or get them to join them instead of going to the gym. They also said that the reasons for their friends’ actions were a lack of knowledge about diabetes and the negative consequences of an unhealthy lifestyle on diabetes control. However, this did not stop them from resisting their friends’ influence [Quotes #19 and #20]. Some non-adherent participants mentioned that co-workers and families exerted strong pressure to engage in being more active and eating healthier. Yet, this increased their resistance, resulting in doing the opposite [Quote #21].

Some non-adherent participants reported experiencing some forms of diabetes stigma, which had a negative influence on adherence to PA/HE and aggravated the emotional and social impact of diabetes. For instance, adolescents at school reported that some peers avoided interacting with them, thinking that they would not be able to have fun with people living with diabetes because of dietary and PA restrictions, regarding their diabetes as a burden because they had to look after them. A couple of adherents reported restrictions in participating in school activities by some teachers [Quote #22]. Other forms of stigmatization originated from parents and health care practitioners, amplifying a sense of blaming, guilt, and personal failure for not following HCP’s advice, regardless of how much they tried [Quote #23]. This negative social influence elicited negative emotions in AYAs such as frustration, anger, and a feeling of being under the control of others. Non-adherent respondents more often mentioned feelings of low self-esteem and social isolation [Quote #24].


Several situations decreased feelings of self-efficacy in non-adherent participants. The first type of situation mentioned was related to social and cultural customs, prompted by the characteristics of the traditional diet and a lack of support from the environment [Quote #25]. A second type of situation was practical in nature, such as: facing difficulty in preparing healthy meals at home or in counting carbohydrates [Quote #26]. A third type of situation encompassed physical situations: non-adherent participants often mentioned encountering physical difficulties in finding suitable places offering healthy food when eating in restaurants or when traveling [Quote #27]. Easy access to unhealthy food was also indicated as facilitating non-adherence [Quote #28]. A fourth type of situation was personal and psychological. Frequently, participants’ erratic lifestyles due to working or studying conditions were mentioned as negatively impacting adherence, as they did not have the time or willpower to find or prepare healthy food. Preferences for unhealthy food accompanied with a dislike for the taste of healthy food were common among them [Quotes #29 and #30].

Concerning PA, a related set of situations were mentioned that often negatively impacted PA adherence. The first type was related to the physical environment. There was a general agreement among non-adherent respondents on the hindering effects of hot weather and infrastructure conditions, such as the availability of and ease of access to places to walk safely, like sidewalks, walking trails, and so on [Quote #31]. A second type concerned practical and personal situations. Time constraints were viewed as a major personal barrier (e.g., when being occupied with studying, work, or handling life matters). Non-adherent participants mentioned specifically fatigue and lack of sleep due to frequent urination as a result of hyperglycemia, and thus having no energy to engage in PA. Additionally, needing a detailed medical evaluation to determine their fitness to practice PA and the need to undertake additional examinations were viewed as complicated processes and barriers to joining gyms. Therefore, they either did not join or they had to deny that they had diabetes. Having babies/young children at home with no place to leave them during PA was mentioned by some mothers [Quote #32]. A third type was psychological in nature. Non-adherents talked about the overwhelming burden of balancing insulin, diet, and PA before, during, and after PA. A common psychological barrier pertaining to non-adherence to both HE and PA is derived from an intrinsic feeling of restriction, intolerance to routine and commitment, feeling down, boredom, and not seeing results [Quote #33]. FoH was linked specifically to PA.

The situations in which adherents found it easy to eat healthily were associated with social, practical, and psychological situations. For instance, eating with the family and having another family member who has diabetes made adherence easier. Other facilitators to HE were having no restrictions on eating, following an easy diet, and having a day off from the diet program [Quote #34].

The situations in which adherent participants found it easy to perform PA were associated with social, practical, physical, and psychological situations. The social situations were when they practiced with family or when they exercised in gyms because they felt supported by a trained coach and other trainees there. In particular, when the gyms were located near their homes [Quote #35]. Common psychological situations that facilitated adherence to both EH and PA were when they were in a good mood, felt motivated, and when located in their own environment [Quote #36 and #37]. Relevant quotes and respondents relating to motivational factors are found in Table 4.

Post-motivational factors

Action planning: Preparatory and coping planning.

Many non-adherent participants indicated wanting to control their diabetes and to achieve their goals through HE and performing more PA, but lacked self-efficacy and did not set clear goals or make action plans [Quote #38]. However, others mentioned making plans, but failed on plan execution, resulting in their plans failing to be realized [Quote #39]. Non-adherents relapsed more often and found it difficult to resist unhealthy stimuli. The main reasons for relapse provided were boredom, laziness, lack of motivation, and not seeing immediate results [Quotes #40 and #41]. Adherent participants did not make many action plans, but if they did, they were mostly linked to registering in a gym, cooking at home, or decreasing the size of food portions in an attempt to follow a diet [Quote #42].

Coping planning.

Non-adherent participants did not make coping plans for the difficult situations they came across when trying to eat healthy; they mentioned relying on increasing the insulin dose to compensate for overeating unhealthy food. Other participants tried to make plans to cut down but not eliminate fast food [Quote #43].

When some adherent participants did make some sort of coping planning, these were mostly connected to plans to decrease portion size and substitute unhealthy food with healthy options, increase their level of PA to compensate for the consumption of extra carbohydrates consumed, and decrease the number of times they went to restaurants [Quote #44].

Similarly, non-adherent participants indicated not making coping plans for adhering to PA, resulting in performing PA inconsistently, sparsely, or never [Quote #45]. However, adherent participants reported making alternative plans, such as trying to manage time by compensating for days missed for PA; increasing the duration of PA; or doing different kinds of PA, such as walking in the shopping mall or swimming instead of vigorous PA [Quote #46].

Distal predisposing factors

Information factors.

The majority of participants, irrespective of whether they were adherents or not, reported that the sources of information available to them were mainly from professionals at diabetes clinics (physicians and diabetes educators) and from the Qatar Diabetes Association. The second common sources were general internet websites, which were in the Arabic language, social media pages, TV, and newspapers [Quote #47]. A couple of adherent participants who used websites specialized in diabetes and traditional methods of media through reading books and journals had followed higher education (university level with medical backgrounds, e.g., pharmacy and nursing).

Some non-adherent participants mentioned friends, mothers, and coaches at gyms as sources of information. Some non-adherent participants looked for diabetes-related information from their friends without diabetes, who in turn used the internet or social media as sources of information. They explained that they did not want to engage in discussions about diabetes with other people living with diabetes, as this would cause them more stress [Quote #48].

Some adherent and non-adherent participants considered the information needed to be updated and modified, because they considered it was complicated, not specific to their situations, and mostly repetitive. They also suggested for the need for more information on what type of exercises are suitable for T1D and on adjusting insulin dose around PA in order to avoid hypoglycemia [Quote #49].

Some participants suggested including PA teachers and other administrative staff in schools in the education about PA and T1D. Others stated that the information related to diabetes and PA was not available to some trainers in the gym. They either did not know how to deal with a hypoglycemic incident, did not have sugary food/drink in the gym, or kept pushing the participant to do more PA without taking their diabetes into consideration [Quote #50]. Relevant quotes and respondents relating to post-motivational and information factors are found in Table 5. The main findings are summarized in Table 6.

Table 5. Interviewee quotes: Post-motivational and distal information factors.


The current study aimed to identify adherence towards HE and PA and the determinants of HE and PA in AYAs with T1D in Qatar. This study supports previous findings which showed that adherence to HE [95,96] and PA [73,96], was suboptimal. It is documented that non-adherence is a common problem in adolescents [9799] and can continue until the mid-twenties [3,100]. Few people were adherent, and in general, those were the older participants. Previous data suggests that, compared to adolescents, young adults could be distinguished by cognitive capacity with more understanding of the consequences of actions [101] and more acceptance of their disease and self-care routine [102]. In the context of Qatar, the rapid socio-economic development and westernization of food habits played an important factor [56,59] and predicted unhealthy dietary habits among Qataris and residents [56]. Moreover, literature reviews from the Arab region revealed that physical inactivity was common among adults [103,104] and adolescents [104] general population. Some of the identified barriers were related to the specific cultural context of this region, such as the availability of and access to exercise facilities, hot weather, and lack of a social support system [103]. On the other hand, Ibrahim and colleagues (2018) found that sports facilities exist in most residential areas across Qatar [105]. However, there is a need for more data on the accessibility, utilization, and evaluation of sports facilities. Additionally, studies showed that Qatari students were less likely to be physically active than non-Qataris [59] and children with T1D were doing fewer outdoor activities [61]. The high prevalence of physical inactivity was associated with socio-economic factors and sedentary behaviors, such as the presence of housemaids, prolonged sitting at work or school, and extensive leisure time on screens (e.g., watching TV, using a computer, or playing video games) [59]. Cultural influences remain an area for future exploration in future research. A couple of participants stated that they adhered to HE but not to PA, or vice versa, because of personal beliefs about the expected outcome of behavior and due to self-efficacy factors. Usually, adherence across domains of diabetes self-management behaviors is not consistent [99,106]. Griva et al. (2000) [107] found that generalized and diabetes-specific self-efficacy among AYAs with T1D were correlated only to adherence to diet but not to PA [107]. Similarly, Mozzillo et al. (2017) [31] found that adherence to PA was lower in AYAs with T1D compared to adherence to diet, reflecting the influence of the disease on daily functioning [31]. Hence, understanding why patients choose to be adherent to PA and not HE or vice versa is needed.

Pre-motivational factors: Awareness and risk perceptions

In this study, the majority of participants reported being cognizant of their own behaviors towards HE and PA. Yet, some non-adherents thought it was acceptable to consume extra-sugary foods as long as they increased their insulin dose. Research demonstrates that engaging in compensatory beliefs can result in maladaptive behavior without a feeling of guilt [108]. Additionally, increasing the daily insulin dose leads to an increase in weight, which further worsens insulin resistance [109,110]. There is some evidence that overweight and obesity are increasingly prevalent in people living with T1D [111,112] and that the focus of patients and HCPs on carbohydrate intake prevailed over the attention paid to the overall HE [22,23,113]. Hence, it is essential to stress the importance of HE to maintain a healthy weight and reduce cardiovascular risks.

Some non-adherent respondents either overestimated their level of diabetes control or were not aware of the need to adjust their behaviors. Thus, they assumed that they were doing well in terms of the level of HbA1c they had achieved, and this did not prompt them to eat healthy or to engage in PA. This correlates with a prior study which found that AYAs with T1D lacked an understanding of the meaning and the implications of the HbA1c test [114] and with previous studies which validated cognition of the need to change behavior as an important predictor of HE [115] and PA behaviors [116]. Quite a few non-adherents reported that they were either intending to change their HE or level of PA or they were in the preparation stage, but there was no committed effort. Previous data showed that people living with T1D in the contemplation and preparation stages were less likely to follow a healthy lifestyle and dietary habits [115,117]. Further, subjects who are in the contemplation stage will not be ready to cope with the disadvantages of new behavior. Therefore, they are more likely to relapse or discontinue [118]. Hence, they may require greater support to realize their actual level of diabetes control and their readiness for or stages of change.

In line with a previous study [119], we found that some participants did not adhere to HE and PA despite their foreknowledge about the risks associated with non-adherence. Joining their peers in social activities and maintaining their social image took priority over controlling their diabetes. While it is expected that higher risk perception should result in higher levels of adherence [120], some studies found that diabetes complications risks not only did not motivate adolescents with T1D to adhere, but were negatively related to adherence, due to low self-efficacy levels [121,122]. Plotnikoff et al. (2010) [123] found that coping appraisal variables (self‐efficacy and response efficacy) were stronger predictors of intention to perform PA in people living with T1D compared to threat appraisal variables (perceived vulnerability and severity) [123]. We also found that some non-adherents did not link susceptibility to or severity of risks of complications to non-adherence. Some studies suggested that patients may continue unhealthy routines due to feelings that bad things will not happen to them [124] or not being convinced of immediate impacts on their health [125]. Previous results showed that AYAs with T1D engage in other risky behaviors, such as insulin and blood glucose monitoring non-adherence [3,126], alcohol use, illicit drug use, smoking, unprotected sex, and disordered eating behaviors [3,127]. Jaser et al. (2011) [127] reported that AYAs often have a lack of understanding and/or misunderstanding that these behaviors may risk their diabetes and health [127]. Beliefs about treatment effectiveness to control diabetes, treatment effectiveness to prevent complications, the perceived consequences and seriousness of diabetes were predictive of better dietary and PA self-management in adults with diabetes [128]. However, studies that examined personal models of diabetes in adolescents with diabetes showed varied results [128130]. A study showed that the greater AYAs perceived their diabetes to be serious, the poorer their dietary self-care behaviors were (PA was not included in the analysis) [129]. Skinner et al., (2001) [130] found that the beliefs about treatment effectiveness to control diabetes has predicted better dietary but not PA self-care behaviors [130]. Neither beliefs about the seriousness of diabetes nor the treatment effectiveness to prevent long-term complications were predictive of HE or PA [130]. In another study, beliefs about treatment effectiveness to control diabetes and treatment effectiveness to prevent complications predicted better HE and PA behaviors, but the perceived threat of diabetes predicted poorer HE and PA [128]. Therefore, comprehensive education on the risks of non-adherence should be tailored to individual patients.

Motivational factors: Attitude, social support, and self-efficacy

In the current study, non-adherents’ advantageous beliefs, unlike adherents’, were not enough to bring them into action. In contrast, some studies found that a more positive attitude improved adherence [131133], while the perceived disadvantages of HE and PA were a major factor affecting non-adherence [134,135]. Three potential explanations could be that: (1) other factors such as low levels of self-efficacy and/or negative social support influenced suboptimal adherence; (2) disadvantages outweigh advantages; according to some participants; failing to see immediate effects of HE and PA on diabetes control has led to discontinuation of healthy behavior. It is known that people living with diabetes may be more likely to change their beliefs and behaviors if they can see how their existing practices lead to healthy outcomes [125,136]; and (3) perhaps the affective component of attitude (emotions created by the prospect of performing a behavior, e.g., feeling deprived of food, or fear of PA-induced hypoglycemia and fear of injuries were more influential on intention to perform behavior than the instrumental component of attitude (cognitive consideration of how advantageous performing a behavior would be). Earlier studies found that respondents with dietary constraints [137,138] and with FoH [139,140] reported not adhering to HE and PA, respectively. Thus, encouraging AYAs with T1D to follow the recommendations of the State of Qatar National Physical Activity Guidelines (NPAG-Q) to seek specialized medical consultation and evaluation before exercising to determine the appropriate progress in the duration and intensity of PA, pre- and post-exercise meals is important to avoid hypoglycemia and injuries [141]. Past observations by other researchers [142,143] reported that measures of affective attitude were more predictive of intention than instrumental attitude. Clearly, further research is needed to examine the influence of attitude on behavior.

Regarding social influences, many non-adherent adolescents reported friends and family as mostly negatively affecting adherence, whereas adherents reported that having good health care and social support systems promoted adherence. Several studies demonstrated similar negative outcomes in social gatherings with peers [119,144]. On the other hand, a systemic review showed that peer involvement improved problem-solving and coping skills among people living with T1D [145]. Research has emphasized that family meal planning and gathering [146,147] and active family participation in PA [148,149] have improved adherence. However, other studies [98,150] found that family conflicts negatively impacted adherence. Thus, families’ education and engagement to support a successful transition of self-management to AYAs and to avoid conflicts is needed. Also, the presence of a well-prepared health care support system increased trust in a provider’s tailored advice and engagement in regular daily HE [151,152] and PA [2,153,154]. Our results indicated that exclusion from school activities has aggravated the emotional and social impact of diabetes, which confirms earlier results [155,156]. The International Society for Pediatric and Adolescent Diabetes (ISPAD) holds the position that adolescents must be able to manage their diabetes in the school setting without being excluded or discriminated [157]. Hence, educating the social environment to create a more supportive atmosphere for people living with diabetes should be enhanced.

Mirroring prior research, the results revealed a range of difficult situations, e.g., eating outside the home [38,158,159] or being busy [132,160162]. Previous research conducted in Qatar demonstrated that the rapid socio-economic development and westernization of food habits also played an important factor in promoting unhealthy eating habits and a sedentary lifestyle [56,59]. Some difficult PA situations were related to the overwhelming burden of balancing insulin, diet, and PA before, during, and after PA, [26,160,163] and to the specific cultural context of this region, such as access to exercise facilities and a hot climate. In Qatar, despite the promising initiatives to promote PA at the national level, like formulating policies and organizing public sports activities such as “National Sports Day” and sports training at federation clubs [103,105], the prevalence of physical inactivity is high among the general youth population [103105]. On the other hand, research has proven that people with T1D with high self-efficacy can motivate themselves [159,164], both directly through efficacy expectations and indirectly through perceived barriers [159], to make healthy food choices [164] and to incorporate PA into their daily routine [149,164,165]. Therefore, strengthening self-efficacy is a prerequisite for improving HE and PA adherence among this age group. Overall, given that motivation and intention are the immediate determinants of action [48] and increased patient motivation has been related to improving HE [44] and PA [166] adherence, it is crucial to assess what motivates AYAs with T1D to adhere to HE and PA recommendations.

Post-motivational factors: Action and coping planning

Our results suggest that action and coping planning were lacking. Many non-adherents reflected on their planning as “implementation intentions” (such as “I plan to join the gym in the summer”) rather than specified action planning. Detailed action planning should describe more than a mere behavioral intention [167,168]. Literature has shown that action planning [48,169] and coping planning [167,170] can be an effective technique to prevent relapse. Araújo-Soares et al. found that action planning and coping planning were predictive of changes in PA in a sample of healthy adolescents [167]. Rohani, et al. (2018) [171] found that action planning and coping planning predicted HE behavior among adults with type 2 diabetes [171]. However, less evidence is available on action and coping planning effects on HE and PA in people living with T1D [172], thus requiring future research. Non-adherent respondents reported inadequate abilities to maintain their efforts towards adherence to PA or HE for a longer period. This could be attributed to the observed deficiencies in coping planning.

Distal factors: Information factors

Regarding information factors, all participants wanted information and diabetes self-management education (DSME) to be tailored to their circumstances and to be continuous. Focus-group interviews by Litchfield and colleagues [154] indicated that the barriers to PA were related to the level of education they got from HCPs. Some non-adherent participants indicated having received contradictory messages regarding PA and HE. In a systematic review, some newly diagnosed T1D patients reported being advised by their HCPs not to exercise [173]. Therefore, it is important to coordinate the messages coming from a variety of sources. Many participants used the internet to look for information on HE and PA. However, these sites were not specific to diabetes and not targeted at AYAs. It is recognized that AYAs tend to use websites and other online resources to find information on diabetes management [12]. A noteworthy finding from the current study was that participants sometimes sought information from people without diabetes. A systematic review [174] revealed that friends and relatives were used as sources of information. Thus, information-seeking behavior from reliable sources should be fostered in AYAs with T1D.

Overall, this study has identified some factors that are known to influence behaviors involved in diabetes management. Furthermore, it has also highlighted determinants in the post-motivational (action planning and coping planning) which are limitedly investigated in T1D. The beneficial effects of these factors in increasing the likelihood of transition of intentions into actions have been demonstrated in various health conditions [170] and in type 2 diabetes [175]. Therefore, more research is required to gain further insight into these factors in T1D to optimize adherence and improve diabetes outcomes. Additionally, it has drawn attention to the needs of Arab patients with diabetes to have reliable educational material and resources in their native language.

Strengths and limitations

This study has some strengths and limitations. First, it has added to our in-depth understanding of the determinants of adherence to HE and PA in young people living with T1D in Qatar, owing to the specificity and depth of the subjective information generated. Second, to minimize researcher bias, all interviews were conducted by the same researcher, who did not have a relationship with the participants. Third, considering the large volume of information generated, adopting a framework analysis approach offered a systematic structure to easily manage, analyze, and identify themes [87].

This study also has some limitations. We recruited 20 participants based on some specific criteria for sample adequacy and verification of richness and saturation. However, it is still conceivable that our sample may not include certain categories. For instance, the views of young people who did not attend the follow-up appointments or were unwilling to participate were missed. These patients may have certain personality traits and views and are an important target for further research. A recent systematic review indicated that younger adults, those with dismissive behavior and preoccupied attachment styles or with anxiety and/or depression, and those who had not attended diabetes education were less likely to attend appointments [176]. Non-attendance was associated with higher HbA1c [176] and with lower adherence to a healthy lifestyle [139,177]. Research suggests that young patients who are less inclined to disclose information regarding their diabetes are likely to be less adherent to diabetes management tasks and have a higher HbA1c [178]. Adolescents tend not to be open to talking about diabetes-related issues because of fear of discrimination and embarrassment. This leads to them missing opportunities to seek help regarding management, implicating the need for a more person-centered approach in T1D education. Nevertheless, it is suggested that the proliferation of qualitative research is the best way to ensure representation, rather than specifying such representation in samples [179]. Second, since saturation was deemed to be achieved, findings from this study may be transferable to similar groups. However, a larger sample size in a quantitative approach is needed to confirm our findings and increase generalizability. Third, while this study has highlighted specific determinants of non-adherence to HE related to insulin pump systems (e.g., some patients found insulin pumps have facilitated the use of corrective dose and gave them more freedom to eat whatever they wanted), we cannot draw enough conclusions on the effect of different types of insulin delivery devices on socio-cognitive factors (e.g., attitude, self-efficacy, etc.), and hence adherence to HE and PA. It was noted previously that insulin pumps offer users the flexibility to adjust insulin basal rates and boluses around exercise [180,181], but whether this has facilitated adherence to PA remains unclear. Therefore, more research is needed in this area to draw further comparisons and conclusions.

Conclusions and recommendations

The suboptimal adherence in AYAs to HE and PA requires more attention. Supportive actions are needed to encourage adherence to a healthy lifestyle to achieve benefits in terms of glycemic control and overall health outcomes, with a special focus on adolescents. Interventions are needed to foster motivation by addressing the relevant determinants to promote adherence to these two behaviors in AYAs with T1D. Such approaches targeting lifestyle modification using modern educational means are particularly important when adherence to HE and PA is pronouncedly low. This study has identified some salient factors for AYAs with diabetes, which can help HCPs identify patients who are most likely to not adhere to HE and PA. The findings encourage diabetes professionals to include friends, family members, and staff at schools and gyms in diabetes education around HE and PA. Additionally, to regularly review the awareness of AYAs with T1D about the risks of non-adherence and identify ways to increase this awareness in a non-threatening manner, review their abilities to make specific action plans to increase and be prepared to cope with challenging situations. Thus, to promote adherence to HE and PA.


The authors are grateful to all the participants who participated in the interviews. The authors would like to thank Hamad Medical Cooperation for providing a grant and the diabetes physicians who helped with participant recruitment. We would also like to thank the diabetes educator, Kawsar Mohamud, for her support in conducting this project, and Entisar Omer, Eman Faisel, and Heba Abo Shahla for assisting in transcribing the interviews.


  1. 1. Maahs DM, West NA, Lawrence JM, Mayer-Davis EJ. Epidemiology of type 1 diabetes. Endocrinol Metab Clin North Am. 2010; 39(3): 481–97. pmid:20723815
  2. 2. Klaprat N, MacIntosh A, McGavock JM. Gaps in knowledge and the need for patient-partners in research related to physical activity and type 1 diabetes: a narrative review. Front Endocrinol (Lausanne). 2019;10: 42–2. pmid:30787908
  3. 3. Peters A, Laffel L; American Diabetes Association Transitions Working Group. Diabetes care for emerging adults: recommendations for transition from pediatric to adult diabetes care systems: a position statement of the American Diabetes Association, with representation by the American College of Osteopathic Family Physicians, the American Academy of Pediatrics, the American Association of Clinical Endocrinologists, the American Osteopathic Association, the Centers for Disease Control and Prevention, Children with Diabetes, The Endocrine Society, the International Society for Pediatric and Adolescent Diabetes, Juvenile Diabetes Research Foundation International, the National Diabetes Education Program, and the Pediatric Endocrine Society (formerly Lawson Wilkins Pediatric Endocrine Society). Diabetes Care;34(11): 2477–85. pmid:22025785
  4. 4. Shahbazi H, Ghofranipour F, Amiri P, Rajab A. Factors affecting self-care performance in adolescents with type I diabetes according to the PEN-3 cultural model. Int J Endocrinol Metab. 2018;16(4): e62582. pmid:30464772
  5. 5. Razavi Z, Karimpourian A, Aramian LM, Bazmamoun H. Demographic characteristics of type 1 diabetic children and adolescents in Hamadan, Iran. J Res Health Sci. 2015;15(3): 196–9. pmid:26411667
  6. 6. Sarant L. The rising tide of type 1 diabetes. Nat Middle East. 2014. 2014. Available from:
  7. 7. Zayed H. Genetic epidemiology of type 1 diabetes in the 22 Arab countries. Curr Diab Rep. 2016;16(5): 37–7.
  8. 8. Habibzadeh F. Type 1 diabetes in the Middle East. The Lancet. 2014;383; editor’s page. Available from:
  9. 9. Ministry of Public Health. Qatar National Diabetes Strategy: preventing diabetes together 2016–2022. 2018. Available from:
  10. 10. Al-Thani A, Farghaly A, Akram H, Khalifa S, Vinodson B, Loares A, et al. Knowledge and perception of diabetes and available services among diabetic patients in the state of Qatar. Cent Asian J Glob Health. 2019;8(1): 333–3. pmid:30881757
  11. 11. Bryden KS, Dunger DB, Mayou RA, Peveler RC, Neil HA. Poor prognosis of young adults with type 1 diabetes: a longitudinal study. Diabetes Care. 2003;26(4): 1052–7. pmid:12663572
  12. 12. Monaghan M, Helgeson V, Wiebe D. Type 1 diabetes in young adulthood. Curr Diabetes Rev. 2015;11(4): 239–50. pmid:25901502
  13. 13. Grant L, Lawton J, Hopkins D, Elliott J, Lucas S, Clark M, et al. Type 1 diabetes structured education: what are the core self-management behaviours? Diabet Med. 2013;30(6): 724–30. pmid:23461799
  14. 14. Caccavale LJ, Nansel TR, Quick V, Lipsky LM, Laffel LM, Mehta SN. Associations of disordered eating behavior with the family diabetes environment in adolescents with type 1 diabetes. J Dev Behav Pediatr. 2015;36(1): 8–13. pmid:25493461
  15. 15. Robert AA, Al-Dawish A, Mujammami M, Dawish MAA. Type 1 diabetes mellitus in Saudi Arabia: a soaring epidemic. Int J Pediatr. 2018;2018: 9408370. pmid:29853923
  16. 16. Kime NH, Pringle A, Rivett MJ, Robinson PM. Physical activity and exercise in adults with type 1 diabetes: understanding their needs using a person-centered approach. Health Educ Res. 2018;33(5): 375–88. pmid:30184073
  17. 17. Gonder-Frederick L. Lifestyle modifications in the management of type 1 diabetes: still relevant after all these years? Diabetes Technol Ther. 2014;16(11): 695–8. pmid:25265471
  18. 18. Patton SR. Adherence to diet in youth with type 1 diabetes. J Am Diet Assoc. 2011;111(4): 550–5. pmid:21443987
  19. 19. Davison K, Negrato C, Cobas R, Matheus A, Tannus L, Palma C, et al. Relationship between adherence to diet, glycemic control and cardiovascular risk factors in patients with type 1 diabetes: a nationwide survey in Brazil. Nutr J. 2014;13(1): 19–9. pmid:24607084
  20. 20. Michaliszyn SF, Faulkner MS. Physical activity and sedentary behavior in adolescents with type 1 diabetes. Res Nurs Health. 2010;33(5): 441–9. pmid:20672318
  21. 21. Mottalib A, Kasetty M, Mar JY, Elseaidy T, Ashrafzadeh S, Hamdy O. Weight management in patients with type 1 diabetes and obesity. Curr Diab Rep. 2017;17(10): 92–101. pmid:28836234
  22. 22. Rovner AJ, Nansel TR, Mehta SN, Higgins LA, Haynie DL, Laffel LM. Development and validation of the type 1 diabetes nutrition knowledge survey. Diabetes Care. 2012;35(8): 1643–47. pmid:22665217
  23. 23. Nansel TR, Lipsky LM, Liu A. Greater diet quality is associated with more optimal glycemic control in a longitudinal study of youth with type 1 diabetes. Am J Clin Nutr. 2016;104(1): 81–7. pmid:27194309
  24. 24. Fortin A, Rabasa-Lhoret R, Lemieux S, Labonté ME and Gingras V. Comparison of a Mediterranean to a low-fat diet intervention in adults with type 1 diabetes and metabolic syndrome: a 6-month randomized trial. Nutr Metab Cardiovasc Dis. 2018;28(12): 1275–84. pmid:30459054
  25. 25. Kennedy A, Nirantharakumar K, Chimen M, Pang TT, Hemming K, Andrews RC, et al. Does exercise improve glycaemic control in type 1 diabetes? A systematic review and meta-analysis. PLoS One. 2013;8(3): e58861. pmid:23554942
  26. 26. Colberg SR, Laan R, Dassau E, Kerr D. Physical activity and type 1 diabetes: time for a rewire? J Diabetes Sci Technol. 2015;9(3): 609–18. pmid:25568144
  27. 27. Lopes Souto D, Paes de Miranda M. Physical excercises on glycemic control in type 1 diabetes mellitus. Nutr Hosp. 2011;26(3): 425–9. pmid:21892557
  28. 28. American Diabetes Association. 13. Children and adolescents: standards of medical care in diabetes-2020. Diabetes Care. 2020;43(Suppl 1): S163–82. pmid:31862756
  29. 29. American Diabetes Association. Standards of medical care in diabetes-2020 abridged for primary care providers. Clin Diabetes. 2020;38(1): 10–38. pmid:31975748
  30. 30. Arguello L, Gustavo AD. Diabetes guidelines implementation toolkit. Thesis, Georgia State University, 2011. Available from:
  31. 31. Mozzillo E, Zito E, Maffeis C, De Nitto E, Maltoni G, Marigliano M, et al. Unhealthy lifestyle habits and diabetes-specific health-related quality of life in youths with type 1 diabetes. Acta Diabetol. 2017;54(12): 1073–80. pmid:28914364
  32. 32. Ministry of Public Health Qatar. National clinical guideline: the diagnosis and management of diabetes mellitus in children and adolescents. 2021. Available from: (2021).
  33. 33. Ministry of Public Health Qatar. National clinical guideline: the diagnosis and management of type 1 diabetes mellitus in adults and the elderly. 2021. Available from: (2021).
  34. 34. American Diabetes Association. Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care. 2007;30: 48–65. pmid:17192379
  35. 35. Pediani L, Bowie P. The benefits of dietitian-led community clinics for people with diabetes: using audit to raise GP awareness. Pract Diabetes Int.1999;16(1): 9–11.
  36. 36. Robson T, Blackwell D, Waine C, Kennedy RL. Factors affecting the use of dietetic services by patients with diabetes mellitus. Diabet Med. 2001;18(4): 295–300. pmid:11437860
  37. 37. Mohammed J, Deda L, Clarson CL, Stein RI, Cuerden MS, Mahmud FH. Assessment of habitual physical activity in adolescents with type 1 diabetes. Can J Diabetes. 2014;38(4): 250–5. pmid:25092645
  38. 38. Alvarado-Martel D, Velasco R, Sánchez-Hernández RM, Carrillo A, Nóvoa FJ, Wägner AM. Quality of life and type 1 diabetes: a study assessing patients’ perceptions and self-management needs. Patient Prefer Adherence. 2015;9: 1315–23. pmid:26396503
  39. 39. Wagner J, Tennen H. Coping with diabetes: psychological determinants of diabetes outcomes. In: Martz H, Livneh H, editors. Coping with chronic illness and disability: theoretical, empirical, and clinical aspects. New York: Springer; 2007. pp. 215–39.
  40. 40. Abu Sabbah K, Al-Shehri A. Practice and perception of self-management among diabetics in Taif, KSA: impact of demographic factors. Int J Med Sci Public Health. 2014;3(1): 264–71.
  41. 41. Kichler C, Moss A, Kaugars AS. Behavioral factors influencing health outcomes in youth with type 1 diabetes. US Endocrinol. 2012;8(2): 77–83.
  42. 42. Sigurdardóttir AK. Self-care in diabetes: model of factors affecting self-care. J Clin Nurs. 2005;14(3): 301–14. pmid:15707440
  43. 43. Conn VS, Hafdahl AR, Lemaster JW, Ruppar TM, Cochran JE, Nielsen PJ. Meta-analysis of health behavior change interventions in type 1 diabetes. Am J Health Behav. 2008;32(3): 315–29. pmid:18067471
  44. 44. Martinez K, Frazer SF, Dempster M, Hamill A, Fleming H, McCorry NK. Psychological factors associated with diabetes self-management among adolescents with type 1 diabetes: a systematic review. J Health Psychol. 2018;23(13):1749–65. pmid:27663288
  45. 45. Cheng LJ, Wang W, Lim ST, Wu VX. Factors associated with glycaemic control in patients with diabetes mellitus: a systematic literature review. J Clin Nurs. 2019;28(9–10):1433–50. pmid:30667583
  46. 46. Neylon OM, O’Connell MA, Skinner TC, Cameron FJ. Demographic and personal factors associated with metabolic control and self-care in youth with type 1 diabetes: a systematic review. Diabetes Metab Res Rev. 2013;29(4): 257–72. pmid:23364787
  47. 47. Wilkinson A, Whitehead L, Ritchie L. Factors influencing the ability to self-manage diabetes for adults living with type 1 or 2 diabetes. Int J Nurs Stud. 2014;51(1): 111–22. pmid:23473390
  48. 48. de Vries H. An integrated approach for understanding health behavior; the I-Change model as an example. Psychol Behav Sci Int J. 2017;2(2): 555–85.
  49. 49. de Vries H, Kremers SP, Smeets T, Brug J, Eijmael K. The effectiveness of tailored feedback and action plans in an intervention addressing multiple health behaviors. Am J Health Promot. 2008;22(6): 417–25. pmid:18677882
  50. 50. Kasten S, van Osch L, Candel M, de Vries H. The influence of pre-motivational factors on behavior via motivational factors: a test of the I-Change model. BMC Psychol. 2019;7(1): 1–12.
  51. 51. de Vries H, Eggers SM, Lechner L, van Osch L, van Stralen MM. Predicting fruit consumption: the role of habits, previous behavior and mediation effects. BMC Public Health. 2014;14: 730–41. pmid:25037859
  52. 52. van Keulen HM, Mesters I, Ausems M, et al. Tailored print communication and telephone motivational interviewing are equally successful in improving multiple lifestyle behaviors in a randomized controlled trial. Ann Behav Med. 2011;41(1): 104–18. pmid:20878293
  53. 53. Cheung K, Eggers S, de Vries H. Combining the integrated-change model with self-determination theory: application in physical activity. Int J Environ Res Public Health. 2021;18(28): 28–41. pmid:33374522
  54. 54. Moreau M, Gagnon M, Boudreau F. Development of a fully automated, web-based, tailored intervention promoting regular physical activity among insufficiently active adults with type 2 diabetes: integrating the I-change model, self-determination theory, and motivational interviewing components. JMIR Res Protoc. 2015;4(1): e25. pmid:25691346
  55. 55. van Het Schip C, Cheung KL, Vluggen S, Hoving C, Schaper NC, de Vries H. Spoken animated self-management video messages aimed at improving physical activity in people with type 2 diabetes: development and interview study. J Med Internet Res. 2020;22(4): e15397. pmid:32324138
  56. 56. Al-Thani M, Al-Thani AA, Al-Mahdi N, Al-Kareem H, Barakat D, Al-Chetachi W, et al. An overview of food patterns and diet quality in Qatar: findings from the national household income expenditure survey. Cureus. 2017;9(5): e1249. pmid:28630807
  57. 57. Donnelly TT, Fung TS, Al-Thani A-ABM. Fostering active living and healthy eating through understanding physical activity and dietary behaviours of Arabic-speaking adults: a cross-sectional study from the Middle East. BMJ Open. 2018;8(4): e019980. pmid:29678976
  58. 58. Donnelly TT, Al-Thani A-ABM, Benjamin K, Al-khater AH, Fung TS, Ahmedna M, et al. Arab female and male perceptions of factors facilitating and inhibiting their physical activity: findings from a qualitative study in the Middle East. PloS One. 2018;13(7): e0199336. pmid:30011280
  59. 59. Al-Thani M, Al-Thani A, Alyafei S, Al-Kuwari MG, Al-Chetachi W, Khalifa SE, et al. Prevalence of physical activity and sedentary-related behaviors among adolescents: data from the Qatar National School Survey. Public Health. 2018;160: 150–5. pmid:29704957
  60. 60. Donnelly TT, Al Suwaidi J, Al Bulushi A, Al Enazi N, Yassin K, Rehman AM, et al. The influence of cultural and social factors on healthy lifestyle of Arabic women. Avicenna. 2011: 3–16.
  61. 61. Bener A, Al-Ali M, Alsaied A, et al. Impact of lifestyle and dietary habits on hypovitaminosis D in type 1 diabetes mellitus and healthy children from Qatar, a sun-rich country. Ann Nutr Metab. 2009;53(3–4): 215–22.
  62. 62. Wiebe DJ, Helgeson V, Berg CA. The social context of managing diabetes across the life span. Am Psychol. 2016;71(7): 526–38. pmid:27690482
  63. 63. Helgeson VS. Young adults with type 1 diabetes: romantic relationships and implications for well-being. Diabetes Spectr. 2017;30(2): 108–16. pmid:28588377
  64. 64. Jaam M, Hadi MA, Kheir N, et al. A qualitative exploration of barriers to medication adherence among patients with uncontrolled diabetes in Qatar: integrating perspectives of patients and health care providers. Patient Prefer Adherence. 2018;12: 2205–16. pmid:30410316
  65. 65. O’Connor C, Joffe H. Intercoder reliability in qualitative research: debates and practical guidelines. Int J Qual Methods. 2020;19: 160940691989922–2.
  66. 66. Rolfe D.E., Ramsden V.R., Banner D. et al. Using qualitative health research methods to improve patient and public involvement and engagement in research. Res Involv Engagem. 2018;4(1): 49–57. pmid:30564459
  67. 67. Christie D, Romano GM, Thompson R, Viner RM, Hindmarsh PC. Attitudes to psychological groups in a paediatric and adolescent diabetes service—implications for service delivery. Pediatr Diabetes. 2008;9(4 Pt 2): 388–92. pmid:18331408
  68. 68. Gardner B, Lally P, Wardle J. Making health habitual: the psychology of ’habit-formation’ and general practice. Br J Gen Pract. 2012;62(605): 664–6. pmid:23211256
  69. 69. Morse J. Determining sample size. Qual Heal Res. 2000;10:3–5.
  70. 70. Guest G, Bunce A, Johnson L. How many interviews are enough?: an experiment with data saturation and variability. Field Methods. 2006;18: 59–82.
  71. 71. Rewers MJ, Pillay K, de Beaufort C, Craig ME, Hanas R, Acerini CL, et al. ISPAD clinical practice consensus guidelines 2014. Assessment and monitoring of glycemic control in children and adolescents with diabetes. Pediatr Diabetes. 2014;15 Suppl 20:102–14. pmid:25182311
  72. 72. Hanas R, John G; International HBA1c Consensus Committee. 2010 consensus statement on the worldwide standardization of the hemoglobin A1c measurement. Diabetes Care. 2010;33(8): 1903–04.
  73. 73. Aschner P, Horton E, Leiter LA, Munro N, Skyler JS; Global Partnership for Effective Diabetes Management. Practical steps to improving the management of type 1 diabetes: recommendations from the Global Partnership for Effective Diabetes Management. Int J Clin Pract. 2010;64(3): 305–15.
  74. 74. Chiang JL, Kirkman MS, Laffel LM and Peters AL; Type 1 Diabetes Sourcebook Authors. Type 1 diabetes through the life span: a position statement of the American Diabetes Association. Diabetes Care. 2014;37(7): 2034–54. pmid:24935775
  75. 75. American Diabetes Association. Standards of medical care in diabetes—2017 Diabetes Care. 2017;40: S1–2.
  76. 76. Saunders B, Sim J, Kingstone T, Baker S, Waterfield J, Bartlam B, et al. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant. 2018;52(4): 1893–907. pmid:29937585
  77. 77. Jaam M. Barriers to medication adherence in patients with uncontrolled diabetes in a primary healthcare setting in Qatar: a mixed method triangulation study. M.Sc. Thesis, Qatar University. 2017. Available from:
  78. 78. Hennink MM, Kaiser BN, Marconi VC. Code saturation versus meaning saturation: how many interviews are enough? Qual Health Res. 2017;27(4): 591–608. pmid:27670770
  79. 79. Vasileiou K, Barnett J, Thorpe S, Young T. Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Med Res Methodol. 2018;18(1): 148–8. pmid:30463515
  80. 80. Francis JJ, Johnston M, Robertson C, Glidewell L, Entwhistle V, Eccles MP, et al. What is an adequate sample size? Operationalising data saturation for theory-driven interview studies. Psychol Health. 2010;25(10): 1229–45. pmid:20204937
  81. 81. Kingstone T. Can sample size in qualitative research be determined a priori? Int J Sci Res. 2018;21(5): 619–34.
  82. 82. Fusch P, Ness L. Are we there yet? Data saturation in qualitative research. Qual Rep. 2015;20(9): 1408–16.
  83. 83. Colberg SR, Sigal RJ, Yardley JE, Riddell MC, David W, Dunstan DW, et al. Physical activity/exercise and diabetes: a position statement of the American Diabetes Association. Diabetes Care. 2016;39(11): 2065–79. pmid:27926890
  84. 84. Gale NK, Heath G, Cameron E, Rashid S, Redwood S. Using the framework method for the analysis of qualitative data in multi-disciplinary health research. BMC Med Res Methodol. 2013;13(1): 1–8. pmid:24047204
  85. 85. Parkinson S, Eatough V, Holmes J, Stapley E, Midgley N. Framework analysis: a worked example of a study exploring young people’s experiences of depression. Qual Res Psychol. 2016;13(2): 109–29.
  86. 86. Nagelhout GE, Hogeling L, Spruijt R, Postma N, de Vries H. Barriers and facilitators for health behavior change among adults from multi-problem households: a qualitative study. Int J Environ Res Public Health. 2017;14(10): 1229–46. pmid:29036936
  87. 87. Hackett A, Strickland K. Using the framework approach to analyse qualitative data: a worked example. Nurse Res. 2019;26(2): 8–13. pmid:30215482
  88. 88. MacPhail C, Khoza N, Abler L, Ranganathan M. Process guidelines for establishing intercoder reliability in qualitative studies. Qual Res. 2015;16(2): 1–15.
  89. 89. Campbell JL, Pedersen OK, Quincy C, Osserman J. Coding in-depth semistructured interviews: problems of unitization and intercoder reliability and agreement. Sociol Methods Res. 2013;42(3):294–320.
  90. 90. Raskind IG, Shelton RC, Comeau DL, Cooper HLF, Griffith DM, Kegler MC. A review of qualitative data analysis practices in health education and health behavior research. Health Educ Behav. 2019;46(1): 32–9. pmid:30227078
  91. 91. Denzin NK, Lincoln YS. Introduction: the discipline and practice of qualitative research. In: Denzin NK, Lincoln YS, editors. Handbook of qualitative research. 3rd Edition, Sage. Thousand Oaks; 2005. pp.1–32.
  92. 92. Elliott V. Thinking about the coding process in qualitative data analysis. Qual Rep. 2018; 23(11): 2850–61.
  93. 93. Morse JM, Barrett M, Mayan M, Olson K, Spiers J. Verification strategies for establishing reliability and validity in qualitative research. Int J Qual Methods. 2002;1(2): 13–22.
  94. 94. Hadi MA, José Closs S. Ensuring rigour and trustworthiness of qualitative research in clinical pharmacy. Int J Clin Pharm. 2016;38(3): 641–6. pmid:26666909
  95. 95. Mackey ER, O’Brecht L, Holmes CS, Jacobs M, Streisand R. Teens with type 1 diabetes: how does their nutrition measure up? J Diabetes Res. 2018;2018: 5094569. pmid:30258854
  96. 96. Piłaciński S, Zozulińska-Ziółkiewicz DA. Influence of lifestyle on the course of type 1 diabetes mellitus. Arch Med Sci. 2014;10(1): 124–34. pmid:24701225
  97. 97. Greene A, Greene S. Chapter 6, adolescence and diabetes: clinical and social science perspectives. In: Allgrove J, Swift P, Greene S, editors. Evidenced-base paediatric adolescent diabetes. Blackwell Publishing. BMJ Books; 2007. pp. 78.
  98. 98. Christie D, Thompson R, Sawtell M, Allen E, Cairns J, Smith F, et al. Structured, intensive education maximising engagement, motivation and long-term change for children and young people with diabetes: a cluster randomised controlled trial with integral process and economic evaluation—the CASCADE study. Health Technol Assess. 2014;18(20): 1–202. pmid:24690402
  99. 99. Gandhi K, Vu BK, Eshtehardi SS, Wasserman RM, Hilliard ME. Adherence in adolescents with type 1 diabetes: strategies and considerations for assessment in research and practice. Diabetes Manag (Lond). 2015;5(6): 485–98. pmid:27066110
  100. 100. Gerstl EM, Rabl W, Rosenbauer J, Gröbe H, Hofer SE, Krause U, et al. Metabolic control as reflected by HbA1c in children, adolescents and young adults with type-1 diabetes mellitus: combined longitudinal analysis including 27,035 patients from 207 centers in Germany and Austria during the last decade. Eur J Pediatr. 2008;167(4): 447–53. pmid:17924142
  101. 101. Cameron FJ, Garvey K, Hood KK, Acerini CL, Codner E. ISPAD clinical practice consensus guidelines 2018: diabetes in adolescence. Pediatr diabetes. 2018;19: 250–61. pmid:29900653
  102. 102. Wolpert HA, Anderson BJ. Young adults with diabetes: need for a new treatment paradigm. Diabetes Care. 2001;24(9): 1513–14. pmid:11522689
  103. 103. Benjamin K, Donnelly TT. Barriers and facilitators influencing the physical activity of Arabic adults: a literature review. Avicenna. 2013: 8–24. / avi.2013.8.
  104. 104. Sharara E, Akik C, Ghattas H, Makhlouf Obermeyer C. Physical inactivity, gender and culture in Arab countries: a systematic assessment of the literature. BMC Public Health. 2018;18(1): 639–58. pmid:29776343
  105. 105. Ibrahim I, Al Hammadi E, Sayegh S, Zimmo L, Al Neama J, Rezeq H, et al. Results from Qatar’s 2018 report card on physical activity for children and youth. J Phys Act Health. 2018;15 Suppl 2: S400–1. pmid:30475130
  106. 106. Quick V, Lipsky LM, Laffel LM, Mehta SN, Quinn H, Nansel TR. Relationships of neophobia and pickiness with dietary variety, dietary quality and diabetes management adherence in youth with type 1 diabetes. Eur J Clin Nutr. 2014;68(1): 131–6. pmid:24253761
  107. 107. Griva K, Myers LB, Newman S. Illness perceptions and self efficacy beliefs in adolescents and young adults with insulin dependent diabetes mellitus. Psychol Health. 2000;15(6): 733–50.
  108. 108. Welch GW, Jacobson AM, Polonsky WH. The problem areas in diabetes scale: an evaluation of its clinical utility. Diabetes Care. 1997;20(5): 760–6. pmid:9135939
  109. 109. Wilcox G. Insulin and insulin resistance. Clin Biochem Rev. 2005;26(2): 19–39. pmid:16278749
  110. 110. Church TJ, Haines ST. Treatment approach to patients with severe insulin resistance. Clin Diabetes. 2016;34(2): 97–104. pmid:27092020
  111. 111. American Diabetes Association. 5. Facilitating behavior change and well-being to improve health outcomes: standards of medical care in diabetes-2020. Diabetes Care. 2020;43 Suppl 1: S48–65. pmid:31862748
  112. 112. Chobot A, Górowska-Kowolik K, Sokołowska M, Jarosz-Chobot P. Obesity and diabetes-not only a simple link between two epidemics. Diabetes Metab Res Rev. 2018;34(7): e3042. pmid:29931823
  113. 113. Mehta SN, Haynie DL, Higgins LA, Bucey NN, Rovner AJ, Volkening LK, et al. Emphasis on carbohydrates may negatively influence dietary patterns in youth with type 1 diabetes. Diabetes Care. 2009;32(12): 2174–6. pmid:19741186
  114. 114. Patiño-Fernández AM, Eidson M, Sanchez J, Delamater AM. What do youth with type 1 diabetes know about the HbA1c test? Child Health Care. 2010;38(2): 157–67. pmid:20563233
  115. 115. Vallis M, Ruggiero L, Greene G, Jones H, Zinman B, Rossi S, et al. Stages of change for healthy eating in diabetes: relation to demographic, eating-related, health care utilization, and psychosocial factors. Diabetes Care. 2003;26(5): 1468–74. pmid:12716806
  116. 116. Plotnikoff RC, Lippke S, Reinbold-Matthews M, Courneya KS, Karunamuni N, Sigal RJ, et al. Assessing the validity of a stage measure on physical activity in a population-based sample of individuals with type 1 or type 2 diabetes. Meas Phys Educ Exerc Sci. 2007;11(2): 73–91.
  117. 117. Vimalavathini R, Agarwal SM, Gitanjali B. Educational program for patients with type-1 diabetes mellitus receiving free monthly supplies of insulin improves knowledge and attitude, but not adherence. Int J Diabetes Dev Ctries. 2008;28(3): 86–90. pmid:19902041
  118. 118. Prochaska JO. Decision making in the transtheoretical model of behavior change. Med Decis Making. 2008;28(6): 845–9. pmid:19015286
  119. 119. Elissa K, Bratt EL, Axelsson ÅB, Khatib S, Sparud-Lundin C. Societal norms and conditions and their influence on daily life in children with type 1 diabetes in the West Bank in Palestine. J Pediatr Nurs. 2017;33: 16–22. pmid:27979497
  120. 120. de Vries H, Mudde A, Leijs I, Charlton A, Vartiainen E, Buijs G, et al. The European Smoking Prevention Framework Approach (EFSA): an example of integral prevention. Health Educ Res. 2003;18(5): 611–26. pmid:14572020
  121. 121. Greening L, Stoppelbein L, Reeves CB. A model for promoting adolescents’ adherence to treatment for type 1 diabetes mellitus. Child Health Care. 2006;35(3): 247–67.
  122. 122. Pereira MG, Almeida AC, Rocha L, Leandro E. Predictors of adherence, metabolic control and quality of life in adolescents with type 1 diabetes. In: Liu Chih-Pin, editors. Type 1 diabetes—complications, pathogenesis, and alternative treatments. Rijeka;2011. pp.119–40.
  123. 123. Plotnikoff RC, Lippke S, Trinh L, Courneya KS, Birkett N, Sigal RJ. Protection motivation theory and the prediction of physical activity among adults with type 1 or type 2 diabetes in a large population sample. Br J Health Psychol. 2010;15: 643–61. pmid:19917151
  124. 124. Patino AM, Sanchez J, Eidson M, Delamater AM. Health beliefs and regimen adherence in minority adolescents with type 1 diabetes. J Pediatr Psychol. 2005;30(6): 503–12. pmid:16055488
  125. 125. Smith B, Frost J, Albayrak M, Sudhakar R. Integrating glucometers and digital photography as experience capture tools to enhance patient understanding and communication of diabetes self-management practices. Pers Ubiquit Comput. 2007;11: 273–86.
  126. 126. Datye KA, Moore DJ, Russell WE, Jaser SS. A review of adolescent adherence in type 1 diabetes and the untapped potential of diabetes providers to improve outcomes. Curr Diab Rep. 2015;15(8): 51–60. pmid:26084580
  127. 127. Jaser SS, Yates H, Dumser S, Whittemore R. Risky business: risk behaviors in adolescents with type 1 diabetes. Diabetes Educ. 2011;37(6): 756–64. pmid:22002971
  128. 128. Skinner TC, Hampson SE, Fife-Schaw C. Personality, personal model beliefs, and self-care in adolescents and young adults with type 1 diabetes. Health Psychol. 2002;21(1): 61–70. pmid:11846346
  129. 129. Skinner TC, John M, Hampson SE. Social support and personal models of diabetes as predictors of self-care and well-being: a longitudinal study of adolescents with diabetes. J Pediatr Psychol. 2000;25(4): 257–67. pmid:10814692
  130. 130. Skinner TC, Hampson SE. Personal models of diabetes in relation to self-care, well-being, and glycemic control. A prospective study in adolescence. Diabetes Care. 2001;24(5): 828–33. pmid:11347738
  131. 131. Liese AD, Ma X, Maahs DM, Trilk JL. Physical activity, sedentary behaviors, physical fitness, and their relation to health outcomes in youth with type 1 and type 2 diabetes: a review of the epidemiologic literature. J Sport Health Sci. 2013;2(1): 21–38.
  132. 132. Lascar N, Kennedy A, Hancock B, Jenkins D, Andrews RC, Greenfield S, et al. Attitudes and barriers to exercise in adults with type 1 diabetes (T1DM) and how best to address them: a qualitative study. PLoS One. 2014;9(9): e108019. pmid:25237905
  133. 133. Karimy M, Koohestani HR, Araban M. The association between attitude, self-efficacy, and social support and adherence to diabetes self-care behavior. Diabetol Metab Syndr. 2018;10: 86–92. pmid:30534204
  134. 134. Palardy N, Greening L, Ott J, Holderby A, Atchison J. Adolescents’ health attitudes and adherence to treatment for insulin-dependent diabetes mellitus. J Dev Behav Pediatr.1998;19(1): 31–7. pmid:9524303
  135. 135. Peyrot M, Rubin RR, Lauritzen T, Snoek FJ, Matthews DR, Skovlund SE. Psychosocial problems and barriers to improved diabetes management: results of the Cross-National Diabetes Attitudes, Wishes And Needs (DAWN) Study. Diabet Med. 2005;22(10): 1379–85. pmid:16176200
  136. 136. Hood KK, Hilliard M, Piatt G, Levers-Landis CE. Effective strategies for encouraging behavior change in people with diabetes. Diabetes Manag (Lond). 2015;5(6): 499–510. pmid:30100925
  137. 137. García-Mayor RV, Larrañaga A. Inadequate coping attitudes, disordered eating behaviours and eating disorders in type 1 diabetic patients. In: Liu Chih-Pin, editor. Type 1 diabetes—complications, pathogenesis, and alternative treatments. IntechOpen; 2011. Available from:
  138. 138. Merwin RM, Moskovich AA, Dmitrieva NO, Pieper CF, Honeycutt LK, Zucker NL, et al. Disinhibited eating and weight-related insulin mismanagement among individuals with type 1 diabetes. Appetite. 2014;81:123–30. pmid:24882448
  139. 139. Riaz M, Basit A, Fawwad A, Yakoob Ahmedani M, Ali Rizvi Z. Factors associated with non-adherence to insulin in patients with type 1 diabetes. Pak J Med Sci. 2014;30(2): 233–9. pmid:24772118
  140. 140. Younk LM, Mikeladze M, Tate D, Davis SN. Exercise-related hypoglycemia in diabetes mellitus. Expert Rev Endocrinol Metab. 2011;6(1): 93–108. pmid:21339838
  141. 141. Aspetar. Qatar National Physical Activity Guidelines. Second edition. 2021. Available from:
  142. 142. Sutton S, French DP, Hennings SJ, Mitchell J, Wareham NJ, Griffin S, et al. Eliciting salient beliefs in research on the theory of planned behaviour: the effect of question wording. Curr Psychol. 2003;22(3): 234–51.
  143. 143. French DP, Sutton S, Hennings SJ, Mitchell J, Wareham NJ, Griffin S, et al. The importance of affective beliefs and attitudes in the theory of planned behavior: predicting intention to increase physical activity. J Appl Soc Psychol. 2005;35(9): 1824–48.
  144. 144. Lehmkuhl HD, Merlo LJ, Devine K, Gaines J, Storch EA, Silverstein JH, et al. Perceptions of type 1 diabetes among affected youth and their peers. J Clin Psychol Med Settings. 2009;16(3): 209–15. pmid:19387802
  145. 145. Akhter K, Turnbull T, Simmons D. A systematic review of parent/peer-based group interventions for adolescents with type 1 diabetes: interventions based on theoretical/therapeutic frameworks. Br J Diabetes. 2018; 18(2): 51–61.
  146. 146. Wylie-Rosett J, Aebersold K, Conlon B, Ostrovsky NW. Medical nutrition therapy for youth with type 1 diabetes mellitus: more than carbohydrate counting. J Acad Nutr Diet. 2012;112(11): 1724–7. pmid:23102172
  147. 147. Smart CE, Annan F, Higgins LA, Jelleryd E, Lopez M, Acerini CL. ISPAD clinical practice consensus guidelines 2018: nutritional management in children and adolescents with diabetes. Pediatr Diabetes. 2018;19 Suppl 27: 136–54. pmid:30062718
  148. 148. Leclair E, de Kerdanet M, Riddell M, Heyman E. Type 1 diabetes and physical activity in children and adolescents. J Diabetes Metab. 2013;1(S10): 1–10.
  149. 149. Wilkie L, Mitchell F, Robertson K, Kirk A. Motivations for physical activity in youth with type 1 diabetes. Pract Diabetes. 2017;34(5): 151–5.
  150. 150. Ye CY, Jeppson TC, Kleinmaus EM, Kliems HM, Schopp JM, Cox ED. Outcomes that matter to teens with type 1 diabetes. Diabetes Educ. 2017;43(3): 251–9. pmid:28520550
  151. 151. Gray A, Threlkeld RJ. Nutritional recommendations for individuals with diabetes. In: Feingold KR, Anawalt B, Boyce A, et al., editors. Endotext. South Dartmouth (MA):, Inc; 2019.
  152. 152. Adu MD, Malabu UH, Malau-Aduli AEO, Malau-Aduli BS. Enablers and barriers to effective diabetes self-management: a multi-national investigation. PLoS One. 2019;14(6): e0217771. pmid:31166971
  153. 153. Kime N, Pringle A, Zwolinsky S, Vishnubala D. How prepared are healthcare professionals for delivering physical activity guidance to those with diabetes? A formative evaluation. BMC Health Serv Res. 2020;20(8): 1–12. pmid:31900136
  154. 154. Litchfield I, Andrews RC, Narendran P, Greenfield S. Patient and healthcare professionals perspectives on the delivery of exercise education for patients with type 1 diabetes. Front Endocrinol (Lausanne). 2019;10: 76–89. pmid:30837947
  155. 155. Kollipara S, Warren-Boulton E. Diabetes and physical activity in school. School Nurse News. 2004;21(3): 12–6. pmid:15171089
  156. 156. Peppa A, Asonitou K, Koutsouki D. Exercise training in students with diabetes: the role of PE teacher at school. SportLogia. 2011; 7(2): 177–84.
  157. 157. Bratina N, Forsander G, Annan F, Wysocki T, Pierce J, Calliari LE, et al. ISPAD clinical practice consensus guidelines 2018: management and support of children and adolescents with type 1 diabetes in school. Pediatr Diabetes. 2018;19 Suppl 27: 287–301. pmid:30084519
  158. 158. Sait G, Kagan G, Ali SC, Umit K, Zehra A, Gurcan K, et al. Comprehensive analysis of health related quality of life in patients with diabetes: a study from Konya Turkey. Turk J Endocrinol Metab. 2007;11: 81–8.
  159. 159. Mohebi S, Azadbakht L, Feizi A, Sharifirad G, Kargar M. Review the key role of self-efficacy in diabetes care. J Educ Health Promot. 2013;2: 36–43. pmid:24083286
  160. 160. Brazeau AS, Rabasa-Lhoret R, Strychar I, Mircescu H. Barriers to physical activity among patients with type 1 diabetes. Diabetes Care. 2008;31(11): 2108–9. pmid:18689694
  161. 161. Hansen UM, Cleal B, Willaing I, Tjørnhøj-Thomsen T. Managing type 1 diabetes in the context of work life: a matter of containment. Soc Sci Med. 2018;219: 70–7. pmid:30391872
  162. 162. Chetty T, Shetty V, Fournier PA, Adolfsson P, Jones TW, Davis EA. Exercise management for young people with type 1 diabetes: a structured approach to the exercise consultation. Front Endocrinol (Lausanne). 2019;10: 326. pmid:31258513
  163. 163. Yardley JE, Brockman NK, Bracken RM. Could age, sex and physical fitness affect blood glucose responses to exercise in type 1 diabetes? Front Endocrinol (Lausanne). 2018;9: 674–85. pmid:30524371
  164. 164. Beckerle CM, Lavin MA. Association of self-efficacy and self-care with glycemic control in diabetes. Diabetes Spectr. 2013;26(3): 172–8.
  165. 165. Johnston-Brooks CH, Lewis MA, Garg S. Self-efficacy impacts self-care and HbA1c in young adults with type I diabetes. Psychosom Med. 2002;64(1): 43–51. pmid:11818585
  166. 166. Dash K, Goyder EC, Quirk H. A qualitative synthesis of the perceived factors that affect participation in physical activity among children and adolescents with type 1 diabetes. Diabet. Med. 2020;00: 1–11. pmid:32181959
  167. 167. Araújo-Soares V, McIntyre T, Sniehotta F. Predicting changes in physical activity among adolescents: the role of self-efficacy, intention, action planning and coping planning, Health Educ Res. 2009; 24(1): 128–39. pmid:18344230
  168. 168. Schwarzer R. Coping planning as an intervention component: a commentary. Psychol Health. 2016;31(7):903–6. pmid:26923503
  169. 169. Poppe L, Van der Mispel C, De Bourdeaudhuij I, Verloigne M, Shadid S, Crombez G. Users’ thoughts and opinions about a self-regulation-based eHealth intervention targeting physical activity and the intake of fruit and vegetables: a qualitative study. PLoS One. 2017;12(12): e0190020. pmid:29267396
  170. 170. Sniehotta F, Schwarzer R, Scholz U, Schuz B. Action planning and coping planning for long-term lifestyle change: theory and assessment. Eur J Soc Psychol. 2005; 35: 565–76.
  171. 171. Rohani H, Bidkhori M, Eslami AA, Sadeghi E, Sadeghi A. Psychological factors of healthful diet promotion among diabetics: an application of health action process approach. Electron Physician. 2018;10(4): 6647–54. pmid:29881527
  172. 172. Swanson V, Maltinsky W. Motivational and behaviour change approaches for improving diabetes management. Pract Diabetes. 2019; 36(4): 121–3.
  173. 173. Kennedy A, Narendran P, Andrews RC, Daley A, Greenfield SM; EXTOD Group. Attitudes and barriers to exercise in adults with a recent diagnosis of type 1 diabetes: a qualitative study of participants in the Exercise for Type 1 Diabetes (EXTOD) Study. BMJ Open. 2018;8(1): e017813. pmid:29371269
  174. 174. Kuske S, Schiereck T, Grobosch S, Paduch A, Droste S, Halbach S, Icks A. Correction to: Diabetes-related information-seeking behaviour: a systematic review. Syst Rev. 2017;6(1): 241. pmid:29202833
  175. 175. Vluggen S, Hoving C, Schaper NC, de Vries H. Exploring beliefs on diabetes treatment adherence among Dutch type 2 diabetes patients and healthcare providers. Patient Edu Couns. 2018;101(1): 92–98. pmid:28729129
  176. 176. Brewster S, Bartholomew J, Holt RIG, Price H. Non-attendance at diabetes outpatient appointments: a systematic review. Diabet Med. 2020;37(9): 1427–42. pmid:31968127
  177. 177. Balkhi AM, Reid AM, Westen SC, Olsen B, Janicke DM, Geffken GR. Telehealth interventions to reduce management complications in type 1 diabetes: a review. World J Diabetes. 2015;6(3): 371–9. pmid:25897348
  178. 178. Easler JK, Haueter HM, Roper SO, Freeborn D, Dyches T. Reasons for open and closed attitudes regarding type 1 diabetes. Diabetes Spectr. 2018;31(1): 37–46. pmid:29456425
  179. 179. Allmark P. Should research samples reflect the diversity of the population? J Med ethics. 2004;30(2): 185–9. pmid:15082815
  180. 180. Tagougui S, Taleb N, Rabasa-Lhoret R. The benefits and limits of technological advances in glucose management around physical activity in patients type 1 diabetes. Front Endocrinol. 2018;9: 818–8. pmid:30713524
  181. 181. Colberg SR, Kannane J, Diawara N. Physical activity, dietary patterns, and glycemic management in active individuals with type 1 diabetes: an online survey. Int J Environ Res Public Health. 2021;18(17):9332–52. pmid:34501920