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Psychometrics properties of type 2 diabetes treatment adherence questionnaire (DTAQ): a study based on Pender’s health promotion model

BMC Endocrine Disorders volume 24, Article number: 157 (2024) Cite this article

Abstract

Background

Management of type 2 diabetes (T2D) as a chronic disease requires treatment adherence such as controlling the blood glucose level and adopting a healthy lifestyle. The present study aimed to develop and psychometrically evaluate a questionnaire based on the Pender’s Health Promotion Model (HPM) to measure treatment adherence and the associated factors among T2D patients.

Methods

The present study was conducted in qualitative and the quantitative phases between March 2022 and March 2023. The participants were T2D patients visiting Shahid Mohammadi hospital Diabetes Clinic in Bandar Abbas in the south of Iran. The first draft of items was extracted from the qualitative phase. The present study used interviews with T2D patients, item construction, validity and reliability evaluation of the instrument, and the relevant statistical analyses. It emphasized the significance of content, face, and construct validity, along with reliability testing using Cronbach’s alpha and test-retest method. Data were analyzed using SPSS software, V16 and AMOS, V23.

Results

A 97-item questionnaire was developed through the qualitative phase and, after content validity, it was reduced to 86 items. Five items were removed in face validation, and after the test-retest method, 79 items were retained. The confirmatory factors analysis confirmed a 65-item model with appropriate fitness of data. Cronbach’s alpha coefficient showed an acceptable reliability of the diabetes treatment adherence questionnaire (α = 0.92).

Conclusion

The questionnaire developed based on the HPM model provides a standard and comprehensive measurement of the degree of adherence to treatment and the associated factors among Iranian T2D patients. This is especially valuable in the Iranian healthcare context, where effective management of chronic diseases such as diabetes is of a top priority. Questionnaires can help identify barriers and facilitators of treatment adherence to inform systematic and goal-oriented interventions. The proposed questionnaire had good psychometric properties, and can be used as a valid and practical instrument to measure the factors related to treatment adherence behaviors.

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Background

The global prevalence of diabetes in adults between 20 and 79 years of age was estimated at 10.5% (536.6 million in number) in 2021, and is also predicted to increase to 12.2% (783.2 million in number) in 2045 [1]. A large-scale study in different geographical areas of Iran showed that 15% of Iranian adults aged 35–70 were estimated to have diabetes and 25.4% had prediabetes [2]. T2D is among the most common metabolic disorders in the world [3].

Treatment adherence is required for the management of type 2 diabetes (T2D) as a chronic disease [4]. Adherence represents how the patient follows the physician’s or healthcare providers’ advice on regularly consuming medicine and living a healthy lifestyle [5]. The treatments that T2D patients are expected to adhere to include a healthy lifestyle, healthy food patterns, increased physical activity and diabetes medication [4, 6]. A systematic review of some developed countries revealed that the prevalence of medication adherence in diabetic patients was between 38.5% and 93.1% [7]. The existing literature showed that diet adherence was also below optimal, with about 40–50% of T2D patients adhering to the proposed dietary guidelines [8, 9]. Concerning the adherence to physical activity, the literature showed the following percentages: 26.4% [10], 60% [11], and 58% [12]. A cross-sectional study in Iran in 2021 found the rate of T2D treatment adherence to be 52.75% [13].

Due to the complexity of treatment adherence behavior, behavior change models can help researchers understand the underlying mechanisms of action to improve them [14]. Effective factors involved in T2D treatment adherence include a wide range of personal, interpersonal and situational factors [15,16,17]. Therefore, to better recognize the determinants of adherence to T2D treatment and develop effective interventions, it is useful to adopt health promotion models that consider the above-mentioned dimensions. Pender’s health promotion model (HPM) is an explanatory model of healthy behavior with a focus on the role of experience in shaping behavior. This model enables health experts to explore a complex biological-psychological-social process that encourages people to adopt health-promoting behaviors [18]. This model helps better understand the factors that determine the behavior and interventions of adherence to treatment in chronic patients, including diabetes [19, 20]. HPM has not only been effective in improving health-promoting behaviors in patients, but can also raise diabetic patients’ awareness and improve psychological functioning, increase their self-efficacy, improve their perceived benefits of health-promoting behaviors, minimize perceived barriers, improve interpersonal support and self-management [21,22,23]. This model consists of three dimensions including individual characteristics and experiences, behavior specific cognition and affect, and behavioral outcomes (Fig. 1).

Fig. 1
figure 1

Pender’s health promotion model

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There are three basic components in HPM that influence health-promoting behavior: (1) individual characteristics and experiences (previous related behavior and personal factors), (2) behavior-specific cognition and affect (perceived benefits of action, perceived barriers of action, perceived self-efficacy, situational influences [24], interpersonal influences and activity-related affect), and (3) desirable health promotion behavior (commitment to a plan of action and immediate competing demands and preferences) [25].

Achieving an accurate measurement instrument for treatment adherence has been as challenging as addressing the underlying factors of non-adherence. Treatment adherence behavior is complicated, multidimensional and influenced by several psychosocial factors including motivation, self-efficacy, beliefs and perceived barriers [26]. Questionnaires exploring factors associated with treatment adherence, along with measuring adherence behavior, can effectively identify the determinants of treatment adherence in T2D patients [27, 28]. Tailored interventions like counseling can then be made to improve adherence.

Treatment adherence measurement methods can be classified as either direct or indirect. Measuring the concentration of a medicine or its metabolites in blood or urine is an example of the direct medication adherence measurement. Examples of the indirect medication adherence measurement are standard questionnaire surveys, counting pills, filling prescriptions, assessing the patient’s clinical outcome, and electronic medication monitors, each with certain strengths and weaknesses [29, 30]. Due to its simplicity and low cost, the questionnaire survey is widely used to measure adherence to treatment in clinical settings [31]. Among the most widely used questionnaires to assess adherence to treatment is Morisky Adherence Scale (MMAS), in two versions, one with four and the other with eight items [32, 33]. This questionnaire specifically assesses the adherence to medication. This measurement instrument and others which measure adherence to treatment adherence in Chronic Diseases Scale (ACDS) [34] and Medication Adherence Report Scale (MARS-5) [35] are not specific to diabetes, and often emphasize the need to adhere to medication. Therefore, it seems necessary to develop a standard questionnaire specifically for adherence to T2D treatment (e.g., medications, diet and physical activity), which was done in the present study.

HPM offers a theoretical framework for exploring the multiple factors affecting health behaviors, such as treatment adherence [36]. The present study sought to provide a comprehensive instrument to measure treatment adherence among T2D patients and the associated factors. The psychometrics of this measurement instrument are strongly needed to ensure the validity and reliability in clinical and research contexts.

Methods

Study design and research population

The present study was conducted in qualitative and the quantitative phases, and was approved by the Ethics Committee of Hormozgan University of Medical Sciences [# IR.HUMS.REC.1400.377], and all patients signed an informed letter of consent.

The present study is actually part of a more comprehensive research project [37] conducted between March 2022 and March 2023. Participants in this study were T2D patients visiting Shahid Mohammadi hospital Diabetes Clinic in Bandar Abbas city, in the south of Iran.

In the first phase, the items were constructed based on a qualitative method, and then in the second phase, the psychometric properties of the scale were tested using a cross-sectional study with T2D patients. The questionnaire was evaluated using a confirmatory factor analysis (CFA) for construct validation. Besides, the reliability was assessed and reported.

Section 1: design and item construction

In the first step, in-depth semi-structured interviews were held following a qualitative directed content analysis based on HPM with 20 patients with T2D in Bandar Abbas [36].

Participants

The participants were T2D patients who visited the Shahid Mohammadi hospital Diabetes Clinic and the private offices of internists and diabetes endocrinologists for treatment. The inclusion criteria were a definitive diagnosis of T2D and a treatment history of at least 1 year, having rich and useful experiences about life with diabetes, willingness to recite prior experiences and the ability to participate in interviews to share information. The participants were included in the study using a purposive sampling method with maximum variation (sex, age, history of diabetes, type of medication, education and occupation).

Data collection

In-depth semi-structured interviews were used for data collection. The interviews were held with 20 T2D patients selected via a purposive sampling in Bandar Abbas, in the south of Iran. Each interview was 20 to 90 min long. The data collection continued until data saturation. At the beginning of each interview, after a self-introduction and revealing the purpose of study, the researcher gained consent from the participants. All interviews were held by the first author, who was fluent in Persian and local languages. The time and place of interview were decided in the participant’s convenience. Permission was gained to audio-record the interview. The interview began with a general question (Please tell me about what life is like with diabetes.) and continued with the relevant content of the model constructs.

Data analysis

The recorded interviews were transcribed verbatim. For an in-depth understanding of the interviews, each transcript was read recurrently and divided into smaller semantic units as codes. The analysis was done using a directed qualitative content analysis and HPM model [38]. The codes were placed in categories that were named according to the HPM constructs, and a new code was given to any text that could not be categorized according to the initial coding plan. The categories were ten in number, nine of which were based on the HPM model constructs and one was external to the model. MaxQDA10 software was utilized to facilitate the organization and analysis of qualitative data.

The initial draft of the questionnaire was developed with 123 items. For instance, a 43-year-old male participant said “When I walk, I feel much better and have a better view of life.” This participant’s statement as the item “I feel mentally better while doing physical activity” was assigned to the perceived benefits construct. These items were reviewed and finally approved by the research team to ensure no overlap and no repetition in multiple sessions. Some duplicates were removed and those that could be merged were done accordingly. Some other items were modified. Eventually, the instrument with 97 items entered the psychometric phase.

Section 2: validity and reliability assessment of instrument

Content validity

Using content validity, evidence can be provided for the extent to which elements of a measurement instruments are relevant to and representative of a given construct for a particular assessment purpose [39].

Quantitative content validity was checked using content validity ratio (CVR) and content validity index (CVI). In this step, the tentative instrument was provided to a panel of 10 experts to assess grammar, phrasing, allocation of items and scaling indicators. The panel of experts consisted of health education and health promotion specialists, internal and endocrinology and metabolism specialists.

To calculate the CVR, a panel of experts was asked to evaluate the necessity of each item in the instrument using a 3-point rating scale (i.e., “The item is necessary”, “The item is useful but not necessary”, or “The item is not necessary”). The CVR was calculated using the following formula:

$$\:\varvec{C}\varvec{V}\varvec{R}=\frac{{\varvec{n}}_{\varvec{e}}-\:\frac{\varvec{N}}{2}}{\frac{\varvec{N}}{2}}$$

  • ne represents the number of experts evaluating an item as necessary for the instrument.

  • N is the total number of experts.

  • Based on Lawshe’s table and the number of experts (n = 10), the value of 0.62 was considered as the minimum acceptable value for the content validity ratio.

To check the CVI index, three criteria of simplicity, relevance and clarity were checked. The experts were asked to rate the items on a 5-point Likert scale. Then, the CVI was calculated using the following formula:

CVI = Number of experts voting (3) or (4) / Total number of experts.

A score of 0.79 and above for each item led to the acceptance of that item.

Face validity

Both quantitative and qualitative measures were taken to test face validity. In the qualitative phase, the questionnaire was provided to ten T2D patients to assess its ambiguity, relevance and difficulty. Next, to remove the inappropriate items and assess the relative importance of each item, a quantitative method was used to test the impact of item. Thus, a 5-point Likert scale was used to rate each item, which included very important (5 points), important (4 points), relatively important (3 points), and relatively unimportant (2 points), and not important at all (1 point). Ten patients were asked to review each item and rate the importance of each on a 5-point Likert scale. The score of each item was then calculated separately using the following formula:

If the impact score was 1.5 or higher, the item was retained for additional analysis.

Impact Score = Frequency (%) ∗ importance.

  • The “Frequency” component indicates the percentage or proportion of patients who perceived a particular item as very important and important, giving it a score of 4 or 5 on a 1–5 Likert scale.

  • The “Importance” component indicates the mean score that the item received across all patient ratings on the same 5-point scale.

Construct validity

The construct validity of questionnaire was tested using CFA. The CFA served a specific purpose. A hypothesis was explicitly formulated for the number of factors, number of indicators and the pattern of placement of items in each factor, and the fit of the desired factor structure in the hypothesis with the structure of the measured covariances was tested [40].

The minimum sample size required for CFA is 5 respondents per item [41]. The sample size was calculated as 395 according to the number of items (79).

The population of diabetes clinic of Shahid Mohammadi Hospital patients was used for sampling. To select participants in the diabetes clinic, the health records were visited and according to the record number, the participants were selected to be included in the study through a systematic sampling. The inclusion criteria for this phase were willingness to participate in the study, having a record in the diabetes clinic of Shahid Mohammadi Hospital as a T2D patient, and residing in Bandar Abbas city.

The data collection occurred in November 2022 to January, 20th, 2023 in the morning and afternoon. To this aim, a researcher-made questionnaire was used. The first author was trained, native and familiar with the data collection method. This author was responsible for the questionnaire completion phase through visiting Diabetes Clinic. T2D patients completed the questionnaires face to face. If a patient failed to fill out the questionnaire due to illiteracy or poor eyesight, the researcher read out the questions in Persian or the local language of convenience. Each questionnaire took about 15 min to complete. To solve any potential problem, the researcher was present in the clinic until the questionnaire completion ended.

The 79-item questionnaire was rated on a five-point Likert scale: strongly agree (5 points), agree (4 points), no idea (3 points), disagree (2 points), and strongly disagree (1 point). The questionnaire consisted of Pender’s HPM constructs and behavior-related experiences (derived from the qualitative research):

Six questions rated the perceived benefits of behavior. Ten questions measured the perceived barriers to behavior. Eleven and eight questions measured perceived self-efficacy and behavior-related affects, respectively. Nine questions measured interpersonal influences and eight measured situational influences. Immediate competing demands and preferences were measured along with seven questions, commitment to plan of action with nine questions, experiences related to behavior with 6 questions, and finally, treatment adherence behavior with five questions.

The fitness of the proposed models for the questionnaire was checked using chi-square (\(\:{\chi\:}^{2}\)), Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), chi-square divided by the degree of freedom, Bentler’s Comparative Fit Index (CFI), Akaike Information Criterion (AIC) and Root Mean Square Error of Approximation (RMSEA). Since each index only indicates a specific aspect of the model fit, several indices are usually used to check the adequacy of the model fit [42]. It should be noted that the GFI and AGFI values are between zero and one, and values greater than 0.9 indicate a good model fit. The CFI is also between zero and one, and the closer it is to one, the better the fitness of the model. Values greater than 0.9 indicate a good fit of the model [43, 44]. RMSEA values less than 0.05 show a good fit. Values around 0.08 indicate an average fit, and values greater than 0.1 indicate poor fit of the model [45]. As for the chi-square, the lower values and non-significance with respect to the degree of freedom indicate a good fitness of the model. It is difficult to use this index in questionnaires with a large number of items [46]. Instead, it is suggested to use the ratio of chi-square to the degree of freedom as a goodness of fit index, with values less than 3 indicating a good model fit [42, 47].

Reliability

To measure the reliability of this measurement instrument, the test-retest method and Cronbach’s alpha were used for each sub-scale of questionnaire and the whole questionnaire. The test and re-test were given to 22 T2D patients visiting the medical centers of Bandar Abbas for healthcare services. Two weeks after the first phase of questionnaire completion, the patients were asked to answer the questions a second time.

Statistical analysis

Data analysis

Data were analyzed using SPSS software, V16 and AMOS, V23. To check the normality of data, Mardia’s multivariate elongation coefficient [48] and the corresponding normalized estimate were used. As the results showed, the estimated value was 835.28 and its normalized estimate was 87.92 (p < 0.001). The estimated values showed that the data were not normally distributed. Thus, the usual maximum likelihood (ML) method could not be used. The Maximum Likelihood with Robust Standard Error method was used instead to estimate the parameters. A CFA was run to test the construct validity of questionnaire in Eq. 6.1 (Bentler). For the reliability check, Cronbach’s alpha test was used.

Ethical considerations

The study was approved by the ethics committee of Hormozgan University of Medical Sciences (#IR.HUMS.REC.1400.377). All participants signed a written informed letter of consent to participate in this study. The participants had the right to withdraw from the study whenever they wanted.

Results

Qualitative results

The participants’ age range in the qualitative phase was between 34 and 75 years with an average value of 56 ± 10.93 years. Their average history of diabetes was 7.87 ± 13.9 years. Totally, 60% of the participants were female and the rest were male. Also, 45% used pills while 25% used insulin, and 30% were both insulin and pill users. As for occupation, 30% of the participants were employed, 45% were housewives, and 25% were retired. In terms of education, 45% of the participants held a Bachelor’s degree or higher. A 97-item questionnaire was developed in the qualitative phase of study.

Content validity

For the qualitative content validation, the content of some items was modified according to experts’ comments. In the quantitative phase, based on the Lawshe’s table, 11 items with a score lower than 0.62 were removed and the rest were retained.

In CVI estimation, based on Waltz & Bausell’s index, all 86 items scored higher than 0.79 entered the face validation phase.

Face validity

In qualitative face validity, 11 items that were reported as difficult to understand were modified. In quantitative face validity, 5 items that scored below 1.5 were removed and finally 81 items were retained for the next step.

Reliability

As the two-week test-retest correlation results showed (see supplementary file), two items from the constructs of perceived benefits with coefficients of 0.476 and situational influences with coefficients of 0.433, were removed and 79 items entered the next step.

Construct validity

A total number of 396 participants with an average age of 54.35 ± 11.47 completely answered the 79-item questionnaire. Their demographic information is summarized in Table 1.

Table 1 Research participants’ demographic information
Full size table

The model tested in the CFA was a 79-item model in 10 dimensions, including treatment adherence benefits, treatment adherence barriers, treatment adherence self-efficacy, treatment adherence related affect, interpersonal influences, situational influences, immediate competing demands and preferences, commitment to plan of action, treatment adherence behavior and treatment adherence experiences. The results of testing the construct validity of the 10-dimensional model are represented in Table 2.

Table 2 Fit indices of confirmatory factor analysis of different models
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As it can be seen in Table 2, the estimated GFI, AGFI and CFI show the primary model did not adequately fit the data. Also, the \(\:{\chi\:}^{2}\)value with the corresponding degree of freedom represented a low model fit (p < 0.001). As previously mentioned, this index was not used for the goodness of fit. But the \(\:{\chi\:}^{2}/df\) and RMSEA indices showed a good fitness of the model. According to these values, in general, this model cannot be considered as a good model. Therefore, the primary model with 79 items was revised after examining the factor loadings and the correlation pattern between items and dimensions. Therefore, 14 items (three items from perceived barriers, three from perceived self-efficacy, one from activity-related affect, two from interpersonal influences, three from situational influences, one from commitment to plan of action and one from experiences) were removed from the model, because their factor loading was less than 0.3. A 65-item model was proposed, whose fit indices were as follows: GFI = 0.96, AGFI = 0.95, 957 CFI = 0.048 and RMSEA = 0.048 with a 90% confidence interval (0.046–0.059), 4614.76 =\(\:{\chi\:}^{2}\) 1970 degrees of freedom (p < 0.001). Based on the relevant values, this model had a good fitness with the data. As the AIC value for this model is 2674.76 and is lower than the same value for the previous model, this 65-item model is the best model (Table 2).

The factor loadings of the revised model with 65 items are shown in Table 3. According to the results in this table, the estimation of all standardized factor loadings was significant at a p-value < 0.05.

Table 3 Factor loadings of items on each dimension of the model estimated through the CFA
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The final ten factors were:

  1. 1.

    Perceived benefits of behavior: include the positive outcomes of adhering to treatment.

  2. 2.

    Perceived barriers to behavior: include the predicted barriers and the costs of showing adherence to treatment.

  3. 3.

    Perceived self-efficacy: represents one’s belief in one’s ability to adhere to treatment.

  4. 4.

    Behavior-related affects: Perceived positive or negative feelings developed before, during and after the treatment adherence behavior.

  5. 5.

    Interpersonal influences: include the effects of knowing what others think about or how they behave concerning treatment adherence.

  6. 6.

    Situational influences: include personal perception and knowledge of a particular situation which can either impede or facilitate a behavior.

  7. 7.

    Immediate competing demands and preferences: represents a competing demand in contrast with the treatment adherence behavior which cannot be avoided or a competing preference which cannot be resisted.

  8. 8.

    Commitment to plan of action: is the intention of employing a planned strategy which leads to the treatment adherence behavior.

  9. 9.

    Experiences related to behavior: comprise one’s own experience or others’ experience of the treatment adherence behavior.

  10. 10.

    Treatment adherence behavior: represents the behavior of following the advice given by healthcare providers.

Table 4 summarizes the results of the reliability test of the questionnaire through Cronbach’s alpha. As the results show, the estimated coefficients for the dimensions range between 0.610 and 0.798, representing good values. The scale score is the result of dividing the mean and standard deviation of each dimension by the number of items, which obtained the lowest mean of 0.63 ± 1.76.

Table 4 Reliability of the dimensions of diabetes treatment adherence questionnaire
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Having removed 32 items from the initial draft of the questionnaire with 97 items, the final version ended up with 65 items. These items were rated on a 5-point Likert scale ranging from strongly agree (5) to strongly disagree (1).

Discussion

The present study aimed to develop a questionnaire to measure T2D patients’ adherence to treatment. The initial draft of the current questionnaire was developed based on a qualitative study. Having removed several items, the final questionnaire was tested and retested. The research findings confirmed the reliability and validity of the questionnaire. As the results showed, 65 items were confirmed after face validity, content validity and construct validity. The items were loaded on 10 factors, treatment adherence benefits, treatment adherence barriers, treatment adherence self-efficacy, treatment adherence related affect, interpersonal influences, situational influences, immediate competing demands and preferences, commitment to plan of action, treatment adherence behavior and treatment adherence experiences. The present findings showed that the current measurement instrument has an adequate reliability and validity. Also, the HPM model proved to be a useful framework for T2D treatment adherence. The present questionnaire can be used to measure the effect of interventions to improve adherence to treatment of this disease.

The perceived barriers and benefits subscales indicate what benefits each patient individually makes from treatment adherence behavior and what barriers they face in adhering to treatment. Each of these subscales is related to medication, physical activity and nutrition. The benefits include the physical and psychological benefits that may occur as a result of T2D treatment adherence. The importance of benefits increases when patients understand they will benefit from making changes and overcoming barriers. In this case, the chances of adopting the healthy behavior are higher [49]. In this regard, Świątoniowska contended that covering topics in patient education, such as treatment goals, benefits and adverse effects, can effectively improve adherence [50]. On the other hand, perceived barriers to treatment adherence include forgetting to take medication, medication side effects, cost issues, and access to medical and diagnostic services and increased appetite. In his study, Rezaei reported daily life challenges and financial challenges as barriers to diabetes treatment adherence [51]. Also, various treatment adherence questionnaires (e.g., Moyski [52] and Modanloo [28]) also expressed the barriers to adherence to medication treatment in their measurement instruments.

In this study, perceived self-efficacy for adherence to treatment is a kind of ability an individual has to show adherence behaviors. Examples are taking medicine and observing nutrition in any situation such as traveling and partying and the ability to deal with the temptations of consuming sugary substances. The adaptability dimension of Modanloo’s questionnaire includes a question “I set my diet according to the recommended diet”. Except for another question about the financial ability to go on a diet, there is no mention of nutrition [28]. A measurement instrument called medication adherence self-efficacy scale (MASES) has been validated in different communities [53,54,55]. It is a 25-item scale to measure patients’ beliefs about their ability to take their medication in different situations. Items were scored from 1 (not at all sure) to 4 (very sure). Higher scores indicate a higher level of self-efficacy. In the aforementioned questionnaire, the emphasis is on medication use and belief in one’s ability to continue taking medicine in different situations, which is included in the proposed measurement instrument in the subscales of situational influences and immediate competing demands and preferences. The construct of situational influences describes conditions that may affect adherence to T2D treatment. Instances of situations are unfavorable weather, travel, party, and upcoming problems for medication, diet, and physical activity. Immediate competing demands and preferences suggest that the individual may compromise treatment adherence in the face of competing conditions such as a favorite TV/Internet program or sleep. Moriski’s questionnaire also deals with the conditions underlying medication adherence behavior. Initially, Morisky et al. developed a self-report scale with four items on common medication consumption behaviors that lead to medication withdrawal [32]. This instrument is currently also used to measure adherence to diabetes treatment [56]. Morisky et al. subsequently added four items to the original version to address conditions affecting adherence behavior to overcome some of the previous limitations. The new scale, the eight-item Morisky Medication Adherence Scale (MMAS-8) consists of eight items, the first seven of which are yes/no questions and the last is a 5-point Likert scale [52]. Different personal, interpersonal and environmental factors [15,16,17] affect a T2D patient’s lifestyle, so there is a need to examine different conditions and also the individuals who actively affect the adherence to treatment in diabetic patients. In the proposed measurement instrument, all questions were rated on a 5-point Likert scale so that the responses could be more wide-ranging. In addition, in the commitment to plan subscale, we extracted items such as planning for the correct and regular use of medicine in different conditions, adherence to the nutrition plan and physical activity.

Interpersonal influences include items such as the effect of trust in healthcare workers and their suggested treatment and adherence to treatment and continue with the influence of family and friends in all three behaviors of medication, physical activity and nutrition. In a qualitative study in Iran, the importance of trusting the healthcare workers and negative experiences in treatment adherence has been also mentioned [51]. In this instrument, in addition to the patient’s friends and relatives, the role of the healthcare workers in adherence to treatment has been pinpointed. Similarly, in the treatment adherence experiences construct, the impact of the individual’s own and others’ experiences on treatment adherence is included.

Among other questionnaires designed in Iran, Madanlo’s treatment adherence questionnaire is one of the most commonly used questionnaires for adherence to treatment of chronic diseases. This questionnaire was developed and psychometrically tested by Madanlu in 2012 with chronic patients. This instrument contains 40 items in several dimensions: interest in treatment, willingness to participate in treatment, ability to adapt, integration of treatment with life, adherence to treatment, and commitment to treatment [28]. The aforementioned dimensions are similar to the items of the following constructs in the present study: commitment to a plan of action, situational influences, and interpersonal influences, self-efficacy and perceived barriers.

People’s mental and emotional state is effective in adherence to treatment, and the behavior-related affects construct and the items we extracted for this construct to address this subject. Reactions to external stressors can cause problems for adherence to treatment recommendations and, more specifically, non-adherence to diet or medication (52). The findings of Alzahrani’s study showed a high level of symptoms of depression, anxiety and stress in patients with T2D [57]. In this construct, one’s feelings about physical activity, diet and taking medicine are stated, and how to accept adherence is measured. One item of this construct is to accept the condition of the disease and adhere to the treatment. Akça Doğan’s study also showed that the level of disease acceptance is related to the level of knowledge about medication adherence, metabolic control, and the risk of diabetic foot in patients with diabetes [58].

Strengths and limitations

In this study, the measurement instrument was developed using a mixed approach to research and from the patients’ point of view. Another strength was the use of the HPM model framework with an emphasis on the type of disease from all aspects. As the results showed, the questionnaire was both reliable and valid to measure the factors affecting adherence to treatment in T2D patients. In the existing literature, the instruments showed not to have been developed to measure these factors, although the questionnaires that were reviewed and discussed had certain strengths and weaknesses. The present study dealt with dimensions that were not considered in other studies. The current instrument was extracted from a qualitative study. The CVI and CVR were used to measure content validity. The results indicate the validity of the questionnaire according to these two indicators. After a confirmatory content analysis, some items were removed. Cronbach’s alpha coefficient of the questionnaire showed an acceptable internal consistency of the measurement instruments. One limitation of study was sampling from one city and completing the questionnaire as a self-report. Also, because participants were selected through a convenience sampling, the generalizability of findings may be limited.

Conclusions

The questionnaire developed based on the HPM model provides a standard and comprehensive instrument to measure the degree of adherence to treatment and the associated factors among T2D patients in Iran. This is especially valuable to the Iranian healthcare context, where effective management of chronic diseases such as diabetes is of top priority. Questionnaires can help identify barriers and facilitators of treatment adherence to inform goal-oriented interventions. The proposed questionnaire had good psychometric properties and can be used as a valid and practical instrument to measure the factors related to treatment adherence behaviors. Researchers can use this instrument to test the effectiveness of intervention programs to improve treatment adherence in these patients.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

T2D:

Type 2 diabetes mellitus

HPM:

Pender’s Health Promotion Model

DTAQ:

Diabetes treatment adherence questionnaire

CFA:

Confirmatory factor analysis

CVR:

Content validity ratio

CVI:

Content validity index

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Acknowledgements

The authors would like to express their gratitude to the funder (HUMS) and participants for their sincere cooperation in this study.

Funding

This project received a research grant from Hormozgan University of Medical Sciences (grant no. 4000362). The funding body (HUMS) was not involved have any role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Authors and Affiliations

  1. Student Research Committee, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Nahid Shahabi

  2. Social Determinants in Health Promotion Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Nahid Shahabi, Zahra Hosseini, Amin Ghanbarnejad & Ahmad Behzad

  3. Cardiovascular Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

    Teamur Aghamolaei

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Contributions

NSH contributed to the design and interview with participants, analysis, interpretation and drafting of the research manuscript. ZH and AB contributed to the design, interpretation and final approval of the manuscript for publication. TA and AGH contributed to the data analysis, interpretation and editing. All authors read and approved the final manuscript.

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Correspondence to Teamur Aghamolaei.

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All methods will be taken in accordance with the declaration of Helsinki. The study is approved by the ethics committee of Hormozgan University of Medical Sciences (# IR.HUMS.REC.1400.377). All participants signed a written informed letter of consent to participate in this study.

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Shahabi, N., Hosseini, Z., Aghamolaei, T. et al. Psychometrics properties of type 2 diabetes treatment adherence questionnaire (DTAQ): a study based on Pender’s health promotion model. BMC Endocr Disord 24, 157 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12902-024-01684-4

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Keywords

BMC Endocrine Disorders

ISSN: 1472-6823

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