Background
Acute coronary syndrome (ACS) is responsible for an estimated annual mortality of 1.8 million individuals (Bueno, 2018). In Thailand, ACS exhibits a mortality rate of 10.0%, with a one-year mortality rate of 39.0% following hospital discharge in 2018 (The Heart Association of Thailand under the Royal Patronage of H.M. the King, 2020). Notably, advancements in ACS treatment have contributed to a reduction in average hospital stay durations. However, it remains imperative for patients to adopt lifestyle modifications as part of secondary prevention. This emphasis arises from recognizing that while treatment interventions can restore blood flow, the underlying atherosclerosis lesions persist (Andres et al., 2012; Piepoli, 2017), thus posing a substantial risk of recurrent cardiac events. Indeed, within one year, approximately 50.0% of patients experience severe heart complications (Briffa et al., 2013; Piepoli, 2017). Consequently, secondary prevention strategies revolve around motivating patients to embrace lifestyle changes, encompassing appropriate physical activity, smoking cessation, adherence to a heart-healthy diet, weight management, optimal blood pressure control, medication compliance, and addressing negative psychosocial factors that may impede behavioral changes. Enhancing outcomes in secondary prevention constitutes a key priority in the recuperation process and the prevention of future adverse events (Brinks et al., 2017; Lichtenstein et al., 2021). Nonetheless, ACS patients encounter challenges in modifying their dietary habits, with a success rate between 19.5% and 26% (Andrikopoulos et al., 2013; Vieira et al., 2012).
Motivation plays a crucial role in driving cognitive activities, cognitive representation, the level of activation or drives for competency, self-determinism, and the persistence of behavior (Bandura, 1978; Carter & Kulbok, 2002). It serves as a catalyst for adopting a healthy diet and initiating and maintaining behavior change (Guertin et al., 2015). Notably, individual motivation exhibits a consistent positive association with the regulation of dietary behaviors (Pelletier et al., 2004).
Motivated individuals are more likely to reduce their consumption of meat or animal products, with dietary motivations closely tied to the underlying reasons for embracing a healthy lifestyle (Brown, 2007). Thus, motivation is paramount as it facilitates ACS patients to adopt healthy dietary behaviors, initiate and sustain behavior change, and ultimately improve their overall health (Guertin et al., 2015). Besides, non-adherence to dietary behaviors has been linked to higher mortality rates from cardiovascular disease (Yu et al., 2018) and has shown associations with hospital readmissions (Mosleh & Darawad, 2015). Conversely, motivation to enhance adherence to dietary behaviors has the potential to improve patients' prognosis and quality of life, reduce the risk of further cardiac events, and decrease overall hospital readmission rates in ACS patients (Li et al., 2014; Singh et al., 2011).
Existing studies on motivation in Thailand have primarily focused on chronic diseases such as diabetes mellitus (DM), hypertension (HT), stroke, chronic kidney disease, asthma, chronic obstructive pulmonary disease (COPD), and psychological conditions. However, limited research has been conducted specifically on motivation for healthy dietary behavior in patients with ACS. Previous prospective studies have revealed that ACS patients tend to modify their eating habits for a brief period, approximately six months, before reverting to their previous unhealthy dietary patterns (de Carvalho et al., 2019; Greco et al., 2020; Twardella et al., 2006).
Hence, there is a need for a dedicated assessment tool to evaluate motivation for dietary behavior in ACS patients. This instrument should possess rationality, simplicity, and convenience in its application. Addressing this requirement, Kato et al. (2021) developed and adapted the Motivation for Healthy Eating Scale (MHES), which allows for the assessment of motivation and the measurement of various types of regulation of eating behaviors. However, such an instrument has not yet been validated for ACS patients in Thailand. Therefore, our study aimed to examine the psychometric validity of the Thai version of the Motivation for Healthy Eating Scale among ACS patients in Thailand. The findings from this research would prove valuable for nurses and healthcare professionals as they seek to assess and measure motivation in this patient population.
Methods
Study Design and Study Participants
This validation study aimed to validate the psychometric properties of the Thai version of the Motivation for Healthy Eating Scale (MHES) among patients with ACS. A total of 200 ACS patients were selected based on the recommended sample size for achieving adequate statistical power in exploratory factor analysis, as suggested by Hair et al. (2010). A multistage random sampling method was employed to select participants from three cardiology outpatient departments in downtown Bangkok hospitals. Inclusion criteria for the sample were as follows: (1) Thai patients diagnosed with ACS who had attended the outpatient cardiac center for a six-month follow-up after the event, (2) aged 20 years or older, (3) absence of cognitive decline, (4) proficiency in reading and writing Thai, and (5) willingness to participate in the research. Exclusion criteria included individuals with unstable conditions such as (1) heart rate outside the range of 50/min to 120/min, (2) respiratory rate outside the range of 8/min to 24/min, (3) blood pressure outside the range of 90/60 mmHg to 140/90 mmHg, or (4) heart failure classified as New York Heart Association (NYHA) functional class 3 or 4.
Instrument Translation and Validation Process
In our research, motivation is conceptually defined as an individual’s perception of the motives behind adhering to healthy dietary behaviors (Pelletier et al., 2004). The initial development of the Motivation for Healthy Eating Scale (MHES) was carried out by Kato et al. (2013), developed based on the Regulations of Eating Behavior Scale (REBS) and self-determination theory (SDT) (Pelletier et al., 2004). Subsequently, a short version of the MHES was created in Japanese and available in English (Kato et al., 2021). For the purpose of validation in our study, the short version of the MHES was used, selected through a consensus process that reflects the face validity of the scale.
The MHES consists of 18 items divided into six subscales: integrated regulation, intrinsic motivation, identified regulation, introjected regulation, external regulation, and amotivation. A combination of positively and negatively worded items was chosen and arranged on a Likert scale, ranging from 1 (Does not correspond at all) to 7 (Corresponds precisely), to capture a range of responses on a self-rating questionnaire. The analysis revealed that the MHES demonstrates satisfactory internal reliability, with Cronbach's alpha values ranging from 0.71 to 0.89 (Kato et al., 2021).
Translation process
The researchers obtained permission from the original developer to utilize the instrument and sought permission to modify it according to the Thai context. Subsequently, the process of translating the scale into Thai commenced. In this phase, the back-translation method was employed, following the approach outlined by Dhamani and Richter (2011).
The translation process involved two instructors from the Chulalongkorn University Language Institute, who are proficient in Thai and English, and an independent translator, a nursing educator specializing in cardiovascular nursing with more than five years of study experience abroad. The researchers compared the original and translated versions in their respective languages, engaged in discussions with the translators and advisors, deliberated on discrepancies, and arrived at a final consensus version. Based on the results of the translation process, it was found that the original and Thai versions of the scale had equivalent interpretations. The researchers detected no translation errors, indicating a successful translation process.
Content validity
The content validity of the final Thai version of the scale was assessed by five experts comprising a cardiologist, a cardiovascular nurse, a nutrition educator, and two nursing instructors. Their expertise ensured the suitability and accuracy of each translated item. The experts were tasked with rating the level of agreement between the items and the provided definitions of the concepts. Based on the experts' evaluation, two items deemed redundant and overlapping meanings were recommended for modification or deletion. Additionally, reducing the scale from 7 to 6 response options was suggested, as individuals often tend to choose the middle option. As a result, the Thai-MHES consisted of sixteen items with Likert scale responses ranging from 1 (does not correspond at all) to 6 (corresponds exactly). The content validity index (CVI) of the MHES was calculated to determine the degree of relevance of the questionnaire items. The average CVI indicated that the Thai-MHES accurately represented the English version, as it achieved a score of 100%. Furthermore, the Thai-MHES demonstrated an item-level content validity index (I-CVI) of 1.0 and a scale-level content validity index (S-CVI) of 1.0, indicating high content validity.
Construct validity and reliability
A pilot test was conducted involving 30 participants with ACS receiving treatment at the cardiology outpatient departments of Police General Hospital in Thailand to finalize the Thai MHES. The internal consistency of the Thai-MHES was assessed using Cronbach's alpha, resulting in a value of 0.73. This indicates that the Thai-MHES exhibited satisfactory reliability, surpassing the recommended threshold of 0.7 for Cronbach's alpha coefficient. To assess the homogeneity of the tool, item-total correlation coefficients were examined. Acceptable coefficients ranged between 0.3 and 0.7. Items with correlation coefficients below 0.3 were considered for deletion, while coefficients above 0.7 indicated redundancy (Hair et al., 2010).
Following the pilot testing, Exploratory Factor Analysis (EFA), specifically employing Principal Component Analysis (PCA) with varimax rotation, was used. Factors with eigenvalues greater than one were extracted to determine the number of factors (Hair et al., 2010). A scree plot was generated, and the cumulative percent of variance was calculated to assess the conceptual adequacy of the extracted factors. Factor loadings of 0.4 or higher, as suggested by Hair et al. (2010), were deemed sufficient to establish a factor.
Data Collection
The data collection for the study was conducted by the researchers between May and August of 2022. Prior to the study, the researchers sought and obtained permission to access the study participants in the cardiology outpatient departments. Patients who met the inclusion criteria and willingly agreed to participate were asked to sign a written consent form. Subsequently, patients were encouraged to complete the Thai-MHES questionnaire. The data collection procedure generally took approximately 10 to 15 minutes per participant.
Data Analysis
Statistical analysis was performed using SPSS Statistics version 29, licensed by Chulalongkorn University. A significance level of 0.05 was considered for determining statistical significance. The construct validity of the Thai-MHES was assessed through exploratory factor analysis (EFA), specifically employing principal component analysis (PCA) with varimax rotation. These analytical techniques were utilized to explore the underlying factors and structure of the Thai-MHES. PCA is a statistical technique used to identify the underlying structure of a set of variables and reduce the data’s dimensionality. It aims to transform a large number of correlated variables into a smaller set of uncorrelated variables called principal components. Each principal component represents a linear combination of the original variables, capturing the maximum amount of variation in the data. While varimax rotation aims to maximize the variance of the factor loadings, leading to a clearer separation between the factors and making it easier to interpret and assign meaningful labels to each factor.
Ethical Considerations
Approval for the study was obtained from the Ethics Committees of the Faculty of Medicine, King Chulalongkorn Memorial Hospital, Siriraj Hospital, and Police General Hospital (IRB No. 0123/65; IRB Protocol No. 354/2565 (IRB4); IRB No. Nq 28/65). The purpose, potential benefits, risks, and duration of the study were thoroughly explained to all participating patients. Prior to their participation in the study, all participants provided their informed consent by signing the appropriate consent forms. By obtaining informed consent, the researchers demonstrated their commitment to protecting the rights, welfare, and autonomy of the participants throughout the research process. This ethical practice helps to ensure that participants are well-informed and willingly engage in the study based on a clear understanding of the study's purpose and potential implications.
Results
Characteristics of the Participants
Table 1 presents the demographic and clinical characteristics of the 200 participants included in this study. The gender distribution indicates that 80.50% of the participants were male, while 19.50% were female. Regarding age, 35.50% of participants were below 60, with the majority (64.50%) being 60 years and above. Marital status varied among the participants, with 71.50% being married as the majority. Education levels were diverse among the participants, with the largest group (34.00%) having completed high school. Regarding financial status, 41.00% of participants reported having no income. Among the participants' diagnoses, 47.50% had ST-elevation myocardial infarction (STEMI), 35.00% had non-ST elevation myocardial infarction (non-STEMI), and 17.50% had unstable angina. Finally, the duration of the participants' cardiac conditions revealed that the majority (47.50%) had a duration of one to five years. These demographic and clinical characteristics provide valuable information about the study sample, allowing for a better understanding of their profiles and potential implications for the research findings.
| Characteristics | n | % |
|---|---|---|
| Gender | ||
| Male | 161 | 80.50 |
| Female | 39 | 19.50 |
| Age (year) | ||
| <60 | 71 | 35.50 |
| >60 | 129 | 64.50 |
| Mean (SD) = 62.20 (8.37) | ||
| Marital status | ||
| Single | 22 | 11.00 |
| Married | 143 | 71.50 |
| Widowed | 20 | 10.00 |
| Divorced | 15 | 7.50 |
| Education level | ||
| No education | 3 | 1.50 |
| Primary school | 39 | 19.50 |
| High school | 68 | 34.00 |
| Associate degree | 10 | 5.00 |
| Bachelor's Degree | 59 | 29.50 |
| Postgraduate | 21 | 10.50 |
| Financial status | ||
| No income | 82 | 41.00 |
| ≤15,000 baht/month | 23 | 11.50 |
| 15,001 – 30,000 baht/month | 49 | 24.50 |
| 30,001 – 45,000 baht/month | 21 | 10.50 |
| 45,001 – 60,000 baht/month | 11 | 5.50 |
| >60,000 baht/month | 14 | 7.00 |
| Diagnosis | ||
| ST-elevation myocardial infarction (STEMI) | 95 | 47.50 |
| Non-ST elevation myocardial infarction (non-STEMI) | 70 | 35.000 |
| Unstable angina | 35 | 17.50 |
| Duration | ||
| Six months – 1 year | 22 | 11.00 |
| 1 – 5 years | 95 | 47.50 |
| 5 – 10 years | 65 | 32.50 |
| >10 years | 18 | 9.00 |
Factor Analysis Results
Prior to conducting EFA, several assumptions were assessed in this study. The evaluation included examining linearity and factorization. The correlation coefficient was 0.73, indicating a moderate positive relationship. Additionally, the Kaiser-Mayer-Olkin (KMO) measure of sampling adequacy was 0.84, indicating that the sample size was appropriate for EFA. Furthermore, Bartlett's test of sphericity was conducted on the correlation matrix of the 16 items, yielding a significant result (χ2 = 1616.44, df = 120, p-value = 0.000). This indicates that the population correlation matrix was not an identity matrix, validating the suitability of EFA for this study.
Based on the results of PCA with varimax rotation, four factors were identified, collectively accounting for 66.78% of the total variance. The communalities of the items ranged from 0.55 to 0.82 within each factor. Specifically, the first four factors explained 40.16%, 11.12%, 8.96%, and 6.54% of the variance, respectively, as shown in Table 2. These findings demonstrate the underlying structure of the data and provide insights into the distinct dimensions captured by the factors.
| Item | Initial Eigenvalues | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | Total | % of Variance | Cumulative % | Communalities | |
| Motivate1 | 6.425 | 40.155 | 40.155 | 6.425 | 40.155 | 40.155 | 3.768 | 23.547 | 23.547 | 0.588 |
| Motivate2 | 1.780 | 11.122 | 51.278 | 1.780 | 11.122 | 51.278 | 2.557 | 15.981 | 39.528 | 0.615 |
| Motivate3 | 1.433 | 8.959 | 60.237 | 1.433 | 8.959 | 60.237 | 2.298 | 14.360 | 53.889 | 0.548 |
| Motivate4 | 1.046 | 6.539 | 66.775 | 1.046 | 6.539 | 66.775 | 2.062 | 12.887 | 66.775 | 0.713 |
| Motivate5 | 0.974 | 6.089 | 72.864 | 0.745 | ||||||
| Motivate6 | 0.711 | 4.446 | 77.311 | 0.654 | ||||||
| Motivate7 | 0.637 | 3.979 | 81.290 | 0.594 | ||||||
| Motivate8 | 0.518 | 3.239 | 84.529 | 0.630 | ||||||
| Motivate9 | 0.445 | 2.782 | 87.311 | 0.758 | ||||||
| Motivate10 | 0.420 | 2.624 | 89.935 | 0.600 | ||||||
| Motivate11 | 0.370 | 2.312 | 92.246 | 0.811 | ||||||
| Motivate12 | 0.305 | 1.904 | 94.151 | 0.626 | ||||||
| Motivate13 | 0.293 | 1.833 | 95.983 | 0.822 | ||||||
| Motivate14 | 0.256 | 1.597 | 97.581 | 0.570 | ||||||
| Motivate15 | 0.216 | 1.347 | 98.928 | 0.702 | ||||||
| Motivate16 | 0.172 | 1.072 | 100.00 | 0.708 | ||||||
Scoring
According to a previous study (Kato et al., 2021), the motivation scale has a maximum score of 96. A higher score on the scale indicates a higher level of motivation. It is worth noting that the previous study did not specifically associate grade levels with the scoring system. Instead, the researchers categorized the scale into three levels: low, moderate, and high motivation, as outlined by Best (1977). Based on this categorization, scores ranging from 16.00 to 42.66 indicate low motivation, 42.67 to 69.33 indicate moderate motivation and 69.34 to 96.00 indicate high motivation. These score ranges provide a framework for interpreting and assessing the participants’ motivation levels in the study context.
Factor Loading
The Thai-MHES, consisting of 16 items, was found to have four factors, as indicated by the factor analysis presented in Table 3. Factor 1, identified as “integrated and integrated regulation,” comprised seven pathway items (Items 1, 2, 7, 8, 10, 12, and 14). Factor 2, termed “intrinsic and external regulation,” consisted of three items (Items 3, 9, and 16). Factor 3, referred to as “introjected regulation,“ included three items (Items 6, 11, and 13). Lastly, Factor 4, labeled “amotivation,” comprised three items (Items 4, 5, and 15). These factors provide a comprehensive understanding of the underlying dimensions and constructs captured by the Thai-MHES, allowing for a more nuanced assessment of participants' motivations.
| Rotated Component Matrix | Factor | |||
|---|---|---|---|---|
| Item | 1 | 2 | 3 | 4 |
| 1. I believe it will eventually allow me to feel better | 0.692 | 0.239 | 0.161 | 0.163 |
| 2. Other people close to me insist that I do | 0.587 | 0.488 | 0.166 | -0.065 |
| 3. It is expected of me | 0.141 | 0.674 | 0.222 | 0.155 |
| 4. I don’t really know. I truly have the impression that I’m wasting my time trying to regulate my eating behaviors | 0.074 | 0.325 | 0.157 | 0.760 |
| 5. I can’t really see I’m getting out of it | 0.348 | 0.050 | 0.084 | 0.784 |
| 6. I feel it is shame not to be able to show healthy eating habits | 0.188 | 0.273 | 0.688 | 0.264 |
| 7. I believe it will make my mind and body comfortable | 0.705 | 0.075 | 0.104 | 0.285 |
| 8. Eating healthy is base of my life | 0.706 | 0.117 | -0.024 | 0.342 |
| 9. I like to find new ways to create meals that are good for the health | 0.232 | 0.796 | 0.069 | 0.257 |
| 10. Eating healthy is an integral part of my life | 0.723 | 0.223 | 0.040 | 0.158 |
| 11. I would be humiliated if I was not in control of my eating behaviors | 0.159 | 0.058 | 0.882 | 0.062 |
| 12. I believe it’s a good thing I can do to feel better about myself in general | 0.735 | 0.188 | 0.111 | 0.194 |
| 13. I would feel ashamed of myself if I was not eating healthy | 0.079 | 0.143 | 0.891 | 0.047 |
| 14. Other people suggestions to keep healthy eating habits | 0.698 | 0.136 | 0.227 | -0.117 |
| 15. I don’t know. I can’t see how my efforts to eat healthy are helping my health situation | 0.224 | 0.500 | 0.155 | 0.615 |
| 16. I take pleasure in fixing healthy meals | 0.285 | 0.770 | 0.112 | 0.146 |
Discussion
This study demonstrated that the Thai-MHES is a reliable and valid tool for assessing motivation in Thai ACS patients. The internal consistency, as measured by Cronbach's alpha, was found to be 0.73, indicating good reliability. The item-total and inter-item correlation coefficients were also deemed appropriate, with values ranging from 0.021 to 0.539 and -0.049 to 0.561, respectively. The reliability analysis of the 16-item perceived value scale showed that most items were worth retaining, as their deletion resulted in a decrease in alpha. Additionally, there were no significant differences in Cronbach's alpha between retaining all items and removing specific ones when the item-total correlation was below 0.30. The findings were consistent with Kato et al. (2021). The item-total correlation coefficient greater than 0.30 was considered acceptable, and inter-item correlations between 0.30 and 0.70 were deemed appropriate. Values ≤0.30 suggested inadequate item provision, while coefficients greater than 0.70 indicated redundancy.
In this study, the translation process of the Thai-MHES was conducted meticulously to ensure the equivalence of the original and translated versions. The use of the back-translation method outlined by Dhamani and Richter (2011) and the involvement of proficient bilingual translators and nursing experts contributed to the successful translation without any detected errors. This rigorous process enhances confidence in the accuracy and interpretation of the Thai version of the scale.
Content validity was assessed by a panel of experts who provided valuable insights and recommendations. Two redundant items with overlapping meanings were identified and suggested for modification or deletion, ensuring the clarity and specificity of the questionnaire. Additionally, reducing the response options from 7 to 6 was recommended to address the tendency of individuals to choose the middle option. The high content validity index (CVI) and item-level content validity index (I-CVI) of 1.0 indicate that the Thai-MHES accurately represents the concepts of the English version and possesses high content validity.
The exploratory factor analysis (EFA) identified four factors that explained a significant portion (66.78%) of the total variance, which is acceptable (Hair et al., 2010), providing evidence for the underlying structure of the data and the distinct dimensions captured by the factors. The factor loadings of 0.4 or higher further support the construct validity of the Thai-MHES.
The four subscales of motivation include introjected regulation, identified and integrated regulation, intrinsic and external regulation, and amotivation. It was noted that the Thai version of the Thai-MHES differed from the original version due to cultural and linguistic distinctions, highlighting the importance of considering these differences when assessing motivation. However, although the Thai version of the Thai-MHES differed from the original version in terms of the subscales, all items reflected and assessed motivation for dietary behavior among ACS patients. Consequently, the Thai-MHES was established as a valid and reliable measure of motivation for Thai ACS patients, specifically in the context of dietary behavior.
The findings of this study have direct implications for nursing practice in the care of ACS patients. Firstly, the availability of reliable and valid Thai-MHES allows nurses to assess and monitor patient motivation accurately. By utilizing this tool, nurses can gain valuable insights into patients' readiness for behavior change related to dietary habits. This knowledge can guide nurses in tailoring interventions and education to address specific motivational factors identified in the assessment, thereby increasing the effectiveness of their interventions and promoting positive health outcomes. Secondly, the study highlights the importance of considering cultural and linguistic distinctions when assessing motivation in Thai ACS patients. Nurses should be aware that the Thai version of the Thai-MHES may differ from the original version in terms of subscales due to these distinctions. This awareness is crucial for understanding and interpreting patient responses accurately. Nurses should adapt their communication and assessment techniques to accommodate cultural nuances and ensure that patients feel understood and supported in their motivation for behavior change. By being culturally sensitive and linguistically competent, nurses can establish a therapeutic relationship with patients and provide patient-centered care that respects their cultural values and beliefs.
Limitations and Recommendations for Future Research
This study has several limitations. Firstly, the study focused specifically on patients with acute coronary syndrome (ACS); therefore, the findings may not be generalizable to individuals with other heart conditions. Future research should aim to test the scale in a broader population of Thai individuals with coronary heart disease, including those who have undergone surgery or have different diagnoses. Secondly, the sample size in this study was limited. A larger sample size would have provided more statistical power to conduct a factor analysis and validate the scale. Hair et al. (2010) suggested that a larger sample size would have enhanced the reliability and robustness of the factor analysis results. Thirdly, the demographic and clinical characteristics of the participants in this study might influence the validity and reliability of the instrument used to assess motivation for behavior change. The gender distribution, with a majority of male participants, might affect the instrument's validity as motivations and factors influencing behavior change can differ between genders. The age distribution is also essential, as motivations can vary across different age groups. In addition, the participants' clinical characteristics, such as diagnoses and duration of cardiac conditions, might also influence motivations for behavior change. The duration of participants' cardiac conditions indicated that the majority (47.50%) had one to five years of duration, which suggests that a significant proportion of the sample had been living with their cardiac condition for a considerable period that can influence individuals' perception of their condition, motivation for behavior change, and self-management strategies (Wiles & Kinmonth, 2001). Considering these characteristics is crucial for future studies to enhance the validity and reliability of the instrument in assessing motivation for behavior change in this population.
Conclusion
This study establishes the Thai-MHES as a reliable and valid tool for assessing motivation in Thai ACS patients, specifically in the context of dietary behavior. The rigorous translation process, thorough assessment of content validity, and successful factor analysis contribute to confidence in the accuracy and interpretation of the Thai version of the scale. Although the Thai version differs in subscales from the original version due to cultural and linguistic distinctions, all items effectively assess motivation for dietary behavior among ACS patients. This study provides valuable insights for nursing practice by enabling nurses to assess patient motivation and tailor interventions accordingly and accurately. Additionally, it emphasizes the importance of cultural competence in nursing care, highlighting the need to consider cultural and linguistic distinctions when assessing and addressing motivation. By incorporating these findings into nursing practice, nurses can optimize patient care and contribute to improved health outcomes.