Assessment of factors influencing physicians’ intention to prescribe transfusion using the theory of planned behavior

doi:10.21203/rs.3.rs-2490590/v1

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Assessment of factors influencing physicians’ intention to prescribe transfusion using the theory of planned behavior

https://doi.org/10.21203/rs.3.rs-2490590/v1

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published 08 Sep, 2023

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Background:

Blood shortage is a persistent problem affecting Taiwan’s health-care system. The theory of planned behavior (TPB) has been commonly used in studies of health advocacy. The purpose of this study was to develop a questionnaire measuring clinicians’ intention to prescribe transfusion based on the TPB.

Method:

A questionnaire comprising 15 items for assessing clinicians’ intention to prescribe blood transfusion was developed, and it collected demographic characteristics tested patient blood management (PBM) and perceived knowledge of PBM. Furthermore, it contained four subscales related to the TPB. A total of 129 clinicians participated in this pilot study between July and December, 2020. Item analysis and exploratory factor analysis were conducted to examine the validity and reliability of this measurement instrument.

Results:

The results indicated no statistically significant correlations between the demographic characteristics and test scores. Regarding perceived knowledge, the results of a one-way analysis of variance revealed that the effect of age, hierarchy of doctors, and education level was significant. In terms of subjective norms, a significant effect for education level was noted [t (129) = 2.28, p < 0.05], with graduate school graduates receiving higher scores than college graduates. An analysis of variance demonstrated the effect of hierarchy, education level, and medical specialty on perceived behavioral control. The results of the regression analyses revealed that perceived knowledge (β = 0.32, p < 0.01) and subjective norms (β = 0.22, p < 0.05) were significantly related to clinicians’ behavioral intention.

Conclusions:

This study revealed that factors affecting clinicians’ blood transfusion management can be explained using the TPB-based questionnaire. This study demonstrated that physicians’ perception of whether most people approve of PBM and their self-assessment of their PBM knowledge affect their intention to proceed with PBM. According to this finding, a support system among physicians must be established and maintained to increase physician’s confidence in promoting PBM.

Transfusion

Physicians’ intention

Behavioral intention

implementation intention

Transfusion provides lifesaving therapeutic benefits for patients with anemia, thalassemia, sickle cell disease, and cancer. Speaking of anemia, it has become more important not only because of the increased prevalence (4.0–7.1% from 2003–2004 to 2011–2012 in United states)[1] but also its association between chronic diseases such as heart failure, fibromyalgia, osteoporosis, chronic inflammation, Alzheimer’s disease, and so on.[2–5] Transfusion is a mainstay in the treatment of anemic patients. It is no surprised that blood transfusions are among the most common procedures performed in Taiwanese hospitals, with a total of 2,149,868 units of red blood cells (RBCs) used in 2015 [6]. Over one in ten hospitalized patients is given a blood transfusion [7].

Blood products are precious and limited resources. Because of population aging and the increasing prevalence of cancer, the demand for blood products has continued to rise over the last two decades. Compared with in 2005, the quantity of RBCs transfused in 2015 increased by 24,085 and 111,860 units in internal medicine divisions and emergency departments, respectively. Blood product availability continues to be a concern. Most blood donors are aged between 30 and 50 years, with the proportion of younger donors being lower than that of older donors. When a severe disaster or pandemic occurs, the shortage of blood products becomes apparent. The Taiwan Blood Services Foundation is raising awareness of the criticality of voluntary blood donation. Moreover, reducing overtransfusion and reviewing inappropriate transfusion practices are essential. The role of patient blood management (PBM) and its clinical application has gradually evolved and gained more attention over the last decades. Meeting patients’ needs individually through optimal evidence-based blood transfusion strategies are at the core of PBM and precision medicine.

Clinicians are accountable for ordering and administering blood products and monitoring transfusion reactions. They are in a key position to detect the signs and symptoms of adverse reactions early. Clinicians follow standard transfusion practices to increase the quality of care. The decision to provide RBC transfusions is based on clinical findings such as signs and symptoms, physical examinations, and laboratory data (e.g., hemoglobin values) [8–10].

Although blood transfusion can be lifesaving and curative, certain risks and complications are associated with the treatment including bloodstream infections, transfusion-related acute lung injury, and coagulation abnormalities. Transfusion can also increase the length of hospital stay, infection rates, complications, and even mortality. Several studies have noted that transfusion does not improve the clinical outcomes of nonbleeding, critically ill patients with anemia. Inappropriate transfusion does not provide any benefits and may even lead to poor outcomes [11], [12].

Numerous guidelines are available to assist practitioners, such as “Clinical Practice Guidelines: Red Blood Cell Transfusion Thresholds and Storage from the American Association of Blood Banks” (AABB) and “the Maximum Surgical Blood Order Schedule.” The Taiwan Blood Services Foundation also provides data on optimal doses and indications of various blood components.

Inappropriate Transfusion

Despite the availability of clinical practice guidelines, significant variability in clinical practice remains. Over half of RBC transfusions may not have been in line with recommended practice. Variability in transfusion practice was identified among hospitals as well as among individual practitioners [13]. This variability indicates that the decision to provide transfusions is based on behavior, individual preferences, rather than scientific data, guidelines, or evidence-based risk versus benefit analysis [14]. Potential barriers between clinical guidelines and physician practices include attitude, lack of self-efficacy, outcome expectancy, and the inertia of previous practice [15].

Avoiding unnecessary blood transfusion not only reduces costs but also improves health-care outcomes [16]. For instance, patients with iron-deficiency anemia (IDA) who received iron supplementation generally had significantly lower hazard ratio for fibromyalgia than those who received blood transfusion alone. On the other hand, iron supplements for hemolytic anemia (HA) may increase the risk of osteoporosis whereas blood transfusions had a lower risk of osteoporosis. Therefore, blood transfusions are not the first line treatment for IDA but are effective for osteoporosis protection in HA.[2, 3] The AABB has education programs and publications for every medical career level worldwide, and most hospitals have their own employee training program. The effectiveness of interventions to reduce physicians’ levels of inappropriate transfusion was identified in several systemic reviews [17–20]. However, no relevant studies have compared the effectiveness and efficiency of existing interventions. The Medical Research Council’s guidance states that the use of evidence and theory-based approaches can assist researchers in understanding the range of possible actions involved in intervention development as well as significantly improve the effectiveness of interventions, thus reducing costs and increasing patients ‘prognosis.[21].

Theory Of Planned Behavior

Ajzen proposed the theory of planned behavior (TPB), a social cognitive theory that links beliefs to behavior [22]. The theory posits that individual behavior is driven by behavioral intention, which is a function of the following three components: attitude, subjective norms, and perceived behavioral control (PBC). Attitude toward behavior can be divided into outcome expectancy and behavioral belief, and subjective norms refer to the perceived social pressure from significant others. PBC relates to factors that can facilitate certain actions, including skills and abilities, time, financial resources, and the cooperation of others. PBC also refers to self-efficacy, which is a person’s belief in their capacity to successfully execute an action.

Various studies have applied the TPB to analyze clinicians’ behavior [23] [24]. Using this theory, numerous studies have described the associations between perceived knowledge, tests of PBM background knowledge, and behavior [25].

Our study assessed the factors that affect clinicians’ behavior in relation to blood transfusion, with two hypotheses proposed. First, the TPB components and knowledge of blood transfusion are associated with clinicians’ behavior toward blood transfusion. Second, the demographic characteristics including education level, hierarchy, and specialty also influence the clinicians’ behavior. The investigation of factors that affect PBM behavior would be valuable and informative for PBM policymakers.

On the basis of the TPB, closed-ended questionnaires in which the participants responded anonymously were designed. The questionnaire designing process followed a published reporting guideline (see Additional file 1) [26]. Nine steps were involved in the development of this questionnaire, from identifying the research purpose, defining the target respondents, selecting the questionnaire methods, designing the questionnaire outline, deciding on the question wording, sequencing the questions, subjecting the questionnaire to expert review, pretesting the questionnaire, and developing the final survey form [27].

We adopted the construct definition of Francis et al., 2009 [16], which contains the following five subscales: (1) demographic characteristics, (2) perceived knowledge and tests of blood transfusion knowledge, (3) attitude toward deliberative transfusion prescription, (4) subjective norms, and (5) PBC. This questionnaire collects the background information of the respondents and contains 64 items related to the aforementioned theoretical domains. Responses were scored on a 5-point Likert scale, with 5 representing strongly agree, and 1 representing strongly disagree.

To ensure content validity, 13 experts were invited to form a panel and judge whether the questionnaire items adequately reflected the intended assessment and measure the items in the domain of interests. Three options (retain, revise, and remove) were provided to the expert panel following their review of each initial item, with a content validity index of greater than 0.8 ensuring expert validity.

Questionnaire Pretest

The simple random sample method was used to obtain adequate samples in the population. Data were collected using online and paper questionnaires from July to December 2020. A total of 229 respondents were recruited in this survey. Following the removal of respondents who were clerks, interns, nurse practitioners, and medical technologists and who therefore could not order blood transfusion for patients; data from 129 respondents, from residents to attending physicians, in Taiwan were collected.

Item analysis and exploratory factor analysis (EFA) were used to explore the factor structure of the questionnaire. EFA is a dimension reduction method analyzing the relationship between the individual item variances and common variances shared between items. Pearson correlation analysis was applied to ensure that each item in the instrument was not highly correlated with each other. In addition, the instrument’s reliability was verified using Cronbach’s alpha, which is used to calculate the correlation between each item and the remaining items or the total number of items. The indicators of item analysis included a critical ratio of greater than 0.3, an item to total correlation of greater than 0.4, a corrected item to total correlation of greater than 0.4, and the Cronbach’s alpha if an item was removed. We removed unsatisfactory items accordingly (questions 18, 27, and 28). The results are summarized in Table 1.

EFA was conducted to explore and verify the items in the questionnaire by identifying the common factors that explain the order and structure among measured variables. In this study, the results of the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test were significant for every dimension, indicating that all the variables were suitable for conducting factor analysis. EFA with orthogonal rotation was performed on the questionnaire’s 21 items. We further removed question 26, 30, and 34 and then performed factor analysis; the results obtained are presented as follows. Following EFA, 15 items were extracted and grouped into four factors, which satisfied the actual purpose as well as the desired purpose (Table 2).

Final Survey Development

After item analysis and EFA, the final questionnaire consisted of 28 items and was divided into three parts (see Additional file 2). Six items in the first part collected the background information of the respondents including their age, gender, education level, and length of service to describe the nature and distribution of the sample used with inferential statistics. In the second part, three items measured perceived knowledge, and four items measured PBM background knowledge. In the third part, we employed TPB-based items, namely four, three, four, and four items assessing the attitudes toward prescribing deliberative transfusion, subjective norms, PBC, and behavioral intention, respectively.

Data Collection And Sample Size

Data were collected using online and paper questionnaires between July and December 2020. This research was conducted using a convenience sample with accessibility taken into consideration. For the questionnaire survey, valid results were edited, coded, and tabulated. Invalid questionnaires with incomplete data or with the same answer to all questions were excluded.

Sample size calculations for the multiple regression analysis depended on the number of cases per predictor variable [28]. Five predictor variables were estimated, which required 146 respondents to test for multiple correlations and 116 to test individual predictor variables.

Data analysis

The SPSS software package was employed for computing descriptive statistics, and an independent-samples t test was applied to identify statistical differences among education levels. One-way analysis of variance (ANOVA) was conducted to compare the theoretical domains among age groups, hierarchies, and medical specialties. Linear regression analysis was performed to determine the relationships between theoretical domains and behavioral intention toward prescribing blood transfusions.

Descriptive statistics

Before the cut-off date of December 3, 2021, 129 valid questionnaires were collected. Respondents (Table 3) were predominately men (72.1%, 93/129). The age group distribution (in years) was as follows: 21–25 years = 26.4%, 26–30 years = 45.7%, 31–35 years = 10.1%, 36–40 years = 7.8%, and over 51 years = 7%. In terms of specialties, surgeons, general practitioners, and internal medicine physicians accounted for 34.1%, 28.7%, and 24.8% of the respondents, respectively.

Seven questions were used to measure knowledge of blood transfusion; four questions related to tests of PBM background knowledge and three related to perceived knowledge of blood transfusion practices. The average test score for participants was 2.78 out of 6 (standard deviation [SD] = 1.02). The correct answer rate of question 10, 11, 12, 13 was 20.9%, 6.2%, 54.3%, and 17.8%, respectively. The mean scores for perceived knowledge, attitude, subjective norms, PBC, and behavioral intention were 2.51, 4.29, 4.20, 3.71, and 4.14, respectively (Table 4). The average score for perceived knowledge was much lower than for the other components of TPB, representing a low level of self-assessment of knowing blood transfusion among the physician respondents.

Table 5 presents the results of the multiple regression of clinicians’ behavioral intention. The scores for perceived knowledge (β = 0.332, p < 0.01) and subjective norms (β = 0.169, p < 0.05) were significantly correlated with clinicians’ behavioral intentions.

The results of the statistical analysis of the theoretical domains are summarized in Tables 6 and 7. No statistically significant correlation was noted between the participants’ demographic characteristics and their test scores for PBM background knowledge. The one-way ANOVA results revealed significant differences in participants’ perceived knowledge of blood transfusion in terms of the age group, hierarchy, and education level. Such perceived knowledge was significantly lower among residents (mean [M] = 2.39, SD = 0.66) than among specialist physicians (M = 2.89, SD = 0.46, p = 0.006). In terms of subjective norms, no significant correlation with demographic characteristics was observed.

The one-way ANOVA results also revealed significant differences in participants’ PBC in terms of hierarchy, education level, and medical specialty. The residents’ PBC score (M = 3.53, SD = 0.68) was significantly lower than that of senior attending physicians (M = 4.15, SD = 0.41), junior attending physicians (M = 4.22, SD = 0.42), and chief residents (M = 4.31, SD = 0.51, F = 9.96, p = < 0.001). Additionally, the average general practitioners’ PBC score (M = 3.35, SD = 0.65) was significantly lower than that of surgeons (M = 3.94, SD = 0.57) and interns (M = 4.02, SD = 0.65, p = < 0.001).

Over the last two decades, the number of publications on factors affecting clinicians’ behavior toward blood transfusion has grown. Our study assessed factors affect clinicians’ behavior toward blood transfusion. A TPB-based questionnaire was developed and verified to be reliable and valid through EFA and item analysis. The results revealed that clinicians’ behavior toward blood transfusion management can be explained using the TPB, with significant correlation among perceived knowledge, subjective norms, and behavioral intention observed. However, the score for PBM behavioral intention exhibited low variation (M = 4.14, SD = 0.52).

In terms of age group, hierarchy, and education level, clinicians’ evaluation of their PBM knowledge significantly differed. The higher was the level of the respondents’ hierarchy, the higher was their score for perceived knowledge. Additionally, with regard to education level, the scores in the graduate school group (M = 2.7, SD = 0.60) were higher than those in the college group (M = 2.33, SD = 0.68). However, the correct answer rate for the test scores for PBM background knowledge was low in this questionnaire, with no significant correlation among demographic characteristics. One explanation is that the questions may have been too difficult; nevertheless, clinicians are relatively lacking in transfusion-related knowledge regarding their identities. This result is consistent with that of a study in 1990 [28], which uncovered widespread deficiencies in physicians’ knowledge of transfusion risks and indicators. Furthermore, the Pearson correlation analysis indicated a weak linear relationship between tests of PBM background knowledge and perceived knowledge (correlation value = 0.02, p = 0.86). One explanation for this is that despite having similar test scores, attending physicians reported higher confidence in their knowledge levels compared with residents.

In terms of subjective norms, medical laboratory scientists, physicians who specialize in transfusion medicine and transfusion committees play key roles in the behavioral intention of clinicians. However, the results revealed no significant correlation between demographic characteristics and subjective norms.

The mean score for PBC was lower than that for attitude and subjective norms (M = 3.71, SD = 0.69). The results revealed significant correlations between PBC and education level, hierarchy, and medical specialty. This finding is expected when less experienced doctors, mainly general practitioners who have so far received only college degrees, have low levels of self-efficacy and less external resources. Moreover, a lack of self-efficacy and familiarity are potentially associated with adherence to guideline recommendations in clinical situations [15]. Although a significant correlation was observed between demographic characteristics and PBC, the effect of PBC on behavioral intention was low. They could be attributed to the strong influence of attending physicians’s advice on their residents’ decisions [29]. The World Medical Association (WMA) Medical Ethics Manual states that physicians are in a profession that traditionally functions in an extremely hierarchical fashion both internally and externally [30]. Research on various medical professions has reported the negative impact of hierarchy, including the generation of moral distress and ethical dilemmas for residents as well as increased risk to patients [31]. The creation of learning environments that encourage residents to voice their opinions is crucial in medical education.

For future behavioral interventions, we recommend focusing on the influence of subjective norms and self-efficacy. Through the organization of multidimensional transfusion education based on real situations, knowledge, PBC, and subjective norms can be improved simultaneously. For example, combined conferences or simulation-based clinical rehearsals increase clinicians’ familiarity with guidelines and transfusion details, which in turn increases their self-efficacy.

The number of hours devoted to learning about transfusion in medical university is low, and the records of continuing education on transfusion are unclear. National policy must emphasize the crucial nature of related education and increase awareness of blood transfusion. Further research into the effectiveness of behavioral intervention using the variable of learning hours instead of demographic characteristic is another method for evaluating clinicians’ behavior.

Several studies have examined the effectiveness of behavioral intervention in modifying health-care practices [17]. However, one study reported that medium-to-large changes in intention lead to a small-to-medium changes in behavior [32]. Although inappropriate transfusion rates would decrease immediately following intervention, these practices would be difficult to sustain and implement for as little as 3 years [33, 34].

A decision support system may improve patient outcomes and safety through reducing inappropriate transfusion; for example, an electronic checklist could be used to assess the need for blood transfusion. Some studies have focused on the effectiveness of an electronic decision support blood order system in reducing inappropriate transfusion and were included in NICE guideline. However, the quality of evidence for all outcomes was low. [35] Along with the spectacular growth of artificial intelligence, the aspect of electronic decision support systems is worth exploring.

The results of this study represent the factors affecting clinicians’ behavior in terms of blood transfusion were obtained using a TPB-questionnaire. The main factors that affect clinicians’ intention toward prescribing blood transfusion in Taiwan were perceived knowledge and subjective norms.

According to these results, we can determine which strategies to implement to increase awareness of the role and implications of PBM among clinicians. Moreover, we can propose promising strategies to persuade collaborators and trainees to apply blood transfusions appropriately.

We plan to further develop the questionnaire items through transnational cooperation. Because of the wide coverage of national health insurance in Taiwan, the cost of blood products is not a major factor affecting clinicians’ behavior. Thus, we removed items related to this when conducting item analysis. Another factor that must be considered is that physicians work in a highly hierarchical fashion in Taiwan. Therefore, comparing the results from Taiwan with those from a different country would be valuable.

Because research into factors affecting blood transfusion in Taiwan was available, this research referred to similar studies with theoretical domain-based frameworks derived from the TPB. However, the respondents of the questionnaires did not represent all medical specialties, and the number of responses among each specialty varied. Therefore, the results cannot be generalized. Thus, collecting comprehensive data from different specialties, staff, and geographical areas in Taiwan is essential.

The sample size in this study was insufficient to perform structural equation modeling or confirmatory factor analysis. Further research in which consequential data collection is initiated is therefore required. Research cooperation with international experts would also enable a comparison of the differences among behaviors affecting blood transfusion practices globally.

Ethics approval and consent to participate

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent was obtained from all subjects and/or their legal guardian(s). This study was approved by the Institutional Review Board of Mackay Memorial Hospital (20MMHIS143e).

Consent for publication

Not applicable.

Availability of data and materials

The data underlying the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that there is no conflict of interest regarding the publication of this paper.

Funding

This work was supported by Mackay Medical College (1082A03), and Department of Medical Research at Mackay Memorial Hospital (MMH-109-79; MMH-109-103).

Authors' contributions

Yu-Han Liao †1, Kung-Pei Tang †, Chih-Yu Chou1, Chien-Feng Kuo†1,3,4, Shin-Yi Tsai

S-YT. had full access to all the data in the study and takes responsibility for the integrity of the data. Study concept and design: S-YT. Acquisition, analysis, or interpretation of data: Y-HL, C-YC, K-PT, and S-YT. Drafting of the manuscript: All authors. Critical revision of the manuscript for important: K-PT and S-YT. Intellectual content: S-YT; Statistical analysis: Y-HL, and K-PT Obtained funding: S-YT, C-FK. Administrative, technical, or material supports: S-YT, Study supervision: S-YT. Submission: Y-HL and S-YT. All authors read and approved the final manuscript.

Acknowledgments

We would like to extend acknowledgment to Associate Professor Po-Fang Tsai, Yung-Shiu Chan, Ming-Tung Wu, Yu-Hua Lin, Ying-Hung Tung, and Chih-Chun Chang's material support, and Department of Medical Research at Mackay Memorial Hospital, and Mackay Medical College for funding support.

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Tables 1 to 7 are available in the Supplementary Files section.

No competing interests reported.

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Assessment of factors influencing physicians’ intention to prescribe transfusion using the theory of planned behavior

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Abstract

Background

Inappropriate Transfusion

Theory Of Planned Behavior

Method

Questionnaire Pretest

Final Survey Development

Data Collection And Sample Size

Data analysis

Results

Descriptive statistics

Discussion

Conclusions

Limitations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1