Paweł Kosowski Polish adaptation of measures of attitudes, subjective norms, perceived behavioral control, and intentions based on the Theory of Planned Behavior in the context of blood donation

Polish Psychological Forum/Polskie Forum Psychologiczne 2025, tom 30, numer 3

DOI: 10.34767/PFP.2025.03.03

Paweł Kosowski¹

¹ Pracownia Psychologii Zdrowia i Jakości Życia, Katedra Psychologii, Wydział Pedagogiki i Psychologii, Uniwersytet Jana Kochanowskiego w Kielcach

https://orcid.org/0000-0002-6552-2729

pawel.kosowski@ujk.edu.pl

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INTRODUCTION

To date, psychological research on voluntary blood donors in Poland remains a niche area has been scarce, with few studies examining the motivations behind blood donation and causes of donor attrition. Understanding these psychological aspects is essential for developing effective recruitment and retention strategies, which directly influence the stability of the national blood donation system. As Poland faces an aging population and an increasing demand for blood, there is a pressing need to explore the determinants shaping both the willingness to donate and the reasons for donor withdrawal. Without such insights, maintaining a stable donor pool may become increasingly challenging.

An analysis of voluntary blood donation statistics in Poland from the past decade highlighted notable fluctuations, particularly during the COVID-19 pandemic and their social and health consequences (Janeczek, 2022). In 2020, the number of donations declined by approximately 9% compared to the previous year, primarily due to pandemic-related disruptions (Supreme Audit Office (NIK), 2024).  By 2023, there were more than 617,000 blood donors, with over 1.5 million donations collected, marking a positive growth trajectory in the blood donation sector (Statistics Poland (GUS, 2024). These trends underscore the vulnerability of the blood donation system to external crises and emphasize the importance of ongoing donor engagement, psychological research, and policy interventions to ensure a resilient and sustainable blood supply.

Due to significant research needs within the group of Polish blood donors, a decision was made to develop a Polish adaptation of the instruments designed to assess motivations for blood donation within the framework of the Theory of Planned Behavior.

The Theory of Planned Behavior in the blood donation context

The Theory of Planned Behavior (TPB), developed by Icek Ajzen (Ajzen, 1991; Ajzen & Madden, 1986), provides a comprehensive framework for understanding the psychological determinants of intentional behaviors, including health-related activities, such as blood donation. TPB posits that an individual’s intention to engage in a behavior is influenced by three core components: (1) attitude toward the behavior, (2) subjective norms, and (3) perceived behavioral control. In the context of blood donation, these components collectively shape a person’s motivation and actual donation behavior.

(1) Attitude encompasses an individual’s positive or negative perception of donating blood, influenced by the beliefs about the effects of blood donation and the value assigned to these effects. For instance, if a person believes that donating blood significantly contributes to saving lives and has a favorable view of this effect, they are more likely to develop a positive attitude toward blood donation. Empirical studies have consistently demonstrated that a favorable attitude is a strong predictor of the intention to donate blood (France et al., 2014; Robinson et al., 2008).

(2) Subjective norms refer to the perceived social pressure to perform or abstain from a behavior, encompassing the influence of family, friends, and societal expectations. If an individual perceives that significant others approve of blood donation, they may feel compelled to conform to these expectations. Research indicates that subjective norms significantly impact blood donation intentions, as individuals often consider the opinions of their social circle when deciding to donate (Giles et al., 2004; Robinson et al., 2008).

(3) Perceived behavioral control reflects an individual’s assessment of their capability to perform the behavior, considering potential facilitators and barriers. In the context of blood donation, factors such as fear of needles, time constraints, or accessibility of donation centers can influence this perception. A higher sense of control is associated with a greater likelihood of intending to donate blood. Studies have found that perceived behavioral control is a significant predictor of both the intention to donate and the actual donation behavior (France et al., 2014).

The Theory of Planned Behavior has been widely applied to study blood donation intentions and behaviors. Empirical research confirms the effectiveness of TPB in predicting donation-related behaviors, incorporating factors such as attitudes, subjective norms, perceived behavioral control, and additional elements like moral norms and donation anxiety. Barbara Masser et al. (Masser et al., 2009) applied an extended TPB model that included moral norms, anticipated regret, donation anxiety, and donor identity. Their study, conducted on 263 experienced blood donors, found that these factors significantly influenced both the intentions and the actual donation behavior. This model accounted for 86% of the variance in donation intentions and 70% of the variance in actual donation behavior, demonstrating robustness of TPB in this context.

Besides the traditional components of the TPB, emotional factors – such as donation anxiety and emotional arousal – play a crucial role in shaping individuals’ intentions to donate blood. Stefanos Balaskas et al. (Balaskas et al., 2024) expanded the TPB framework by integrating these emotional dimensions, demonstrating that both positive and negative emotional arousal significantly influence donation intentions. Their findings suggest that mitigating emotional barriers and fostering positive emotional experiences can effectively enhance blood donation behaviors. In a similar context, Antoine Beurel-Tréhan et al.(2025) examined deterrents to engage in plasmapheresis donation using TPB as a conceptual framework. Their research investigated interventions aimed at converting whole-blood donors into plasma donors. The study assessed the effectiveness of experimental communication strategies, such as redesigned informational materials, in shaping donor attitudes and perceptions of control over the plasmapheresis process. Its findings indicated that clear, engaging, and transparent donor educational materials significantly increased willingness to participate in plasma donation. These insights underscore the importance of persuasive communication and tailored messages in influencing donors’ decision to donate.

Addressing another critical issue in donor retention, Roberto Espinoza Chamorro et al.(2024) investigated the potential of gamification in overcoming blood donation deferrals, a common challenge that negatively impacts donor return rates. Their study examined whether digital engagement tools – such as interactive feedback and reward-based systems – could positively influence donors’ attitudes and perceived control over the donation process. Using TPB as a theoretical framework, the researchers found that gamification significantly alleviated the negative emotions associated with deferrals and reinforced donors’ intentions to return for future donations. These findings highlight the potential of interactive digital interventions in reducing psychological barriers that contribute to donor attrition.

Similarly, a narrative review by Rabeya Tariq et al.(2024) synthesized findings from multiple studies to examine the psychological factors that encourage or discourage voluntary blood donation. The authors emphasized the role of subjective norms, revealing that individuals are more likely to donate when social approval and community expectations align with their personal beliefs. Additionally, the review identified misconceptions and fear as key barriers, suggesting that public education and targeted awareness campaigns – grounded in the TPB framework – could effectively increase donor participation. These findings underscore the critical role of social influence and information dissemination in shaping blood donation behaviors.

ORIGINAL TOOL

The authors developed a tool based on the Theory of Planned Behavior to assess psychological factors influencing blood donation behavior. The tool consists of four scales: (1) Donation Attitude – a six-item scale with a two-factor structure; (2) Subjective Norm – a six-item scale with a two-factor structure; (3) Perceived Behavioral Control – a six-item scale with a two-factor structure; (4) Donation Intention – a three-item scale with a one-factor structure. Each scale was designed to measure key TPB constructs in a standardized and reliable way (France et al., 2014).

The validation process involved two independent studies. The first study was conducted on a sample of 1,080 university students, in which exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to establish the structural validity of the scales. The second study was conducted on 433 experienced blood donors. This study included additional CFA and structural equation modeling (SEM) to confirm the tool’s predictive validity. The results indicated a good model fit (CFI = .976; RMSEA = .041; SRMR = .055), with the TPB model accounting for 73.7% of the variance in donation intention.

A comprehensive review of the literature revealed no previous adaptations of the presented tool.

METHOD

Participants

The present study included 422 participants from various regions of Poland. Of these, 299 (70.9%) were women, 121 (28.7%) were men, and 2 (0.4%) identified as “other,” including non-binary or asexual individuals. The participants’ ages ranged widely, with the mean age of 26.81 years (SD = 10.62).

As regards the place of residence, 140 participants (33.2%) lived in large cities (population > 100,000), 63 participants (14.9%) resided in small towns (population < 20,000), 63 participants (14.9%) were from medium-sized towns (population between 20,000 and 100,000), and 156 participants (37.0%) lived in rural areas.

In terms of educational and professional status, the sample included 175 non-working students (41.5%), 141 full-time employees (33.4%), 57 working students (13.5%), 28 adult high school students (6.6%), 12 unemployed individuals (2.8%), 3 prison service officers (0.7%), and 2 retirees (0.5%).

As regards the relationship status, 144 participants (34.1%) were single, 177 (41.9%) were in informal relationships, 88 (20.9%) were in formalized relationships, 10 (2.4%) were divorced, and 3 (0.7%) were widowed.

Measures used

To evaluate the external consistency of the adapted instruments, six measures were used: (1) The Light Triad Scale (TLS), (2) Flourishing Scale (FS), (3) Generalized Self-Efficacy Scale (GSES), (4) The Revised NEO Personality Inventory (NEO-PI-R) subscales, (5) Ten Item Personality Inventory (TIPI), (6) The Gratitude Questionnaire – Six Item Form (GQ-6).

• The Light Triad Scale (Gerymski & Krok, 2019; Kaufman et al., 2019) is a 12-item Likert-type questionnaire assessing three benevolent personality traits – Faith in Humanity, Humanism, and Kantianism – reflecting a caring and altruistic orientation towards others. Reliability coefficients for the present study were: Cronbach’s a = .82 and McDonald’s w = .83.
• The Flourishing Scale is an 8-item, Likert-type questionnaire (Diener et al., 2010). This scale provides a summary measure of an individual’s self-perceived success in key areas such as relationships, self-esteem, purpose, and optimism, offering a single psychological well-being score. Reliability coefficients for the present study were: Cronbach’s a = .91 and McDonald’s w = .91.
• Generalized Self-Efficacy Scale (Juczyński, 2001; Schwarzer & Jerusalem, 1995) is a 10-item scale assessing an individual’s general belief in their ability to handle various challenging and novel situations effectively. Reliability coefficients for the present study were: Cronbach’s a = .90 and McDonald’s w = .90.
• The Revised NEO-Personality Inventory (NEO-PI-R)(Costa Jr & McCrae, 2000; Siuta, 2006) is a comprehensive inventory that measures five major domains of personality –Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness – providing a detailed profile of an individual’s personality traits. The following subscales were extracted from the NEO-PI-R: Kindness from the Extraversion scale, Feelings, Actions, and Ideas from the Openness to Experience scale, and Altruism from the Agreeableness scale. Reliability coefficients for the present study were: Cronbach’s α = .85 and McDonald’s ω = .88.
• Ten Item Personality Inventory (Gosling et al., 2003; Sorokowska et al., 2014) is a short, ten-item measure designed to assess the Big Five personality traits: Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness to Experience. Despite its brevity, it provides a useful and efficient evaluation of core dimensions of personality. Reliability coefficients for the present study were: Cronbach’s α = .52 and McDonald’s ω = .60.
• The Gratitude Questionnaire – Six Item Form (Kossakowska & Kwiatek, 2014; McCullough et al., 2002). The GQ-6 is designed to measure individual differences in gratitude as a trait. It evaluates how frequently and intensely a person feels gratitude in their daily life, providing insights into a positive orientation towards life’s experiences. Reliability coefficients for the present study were: Cronbach’s α = .76 and McDonald’s ω = .78.

Translation procedure

Initially, the corresponding author of the original tool, Christopher France, was contacted for permission to conduct the validation and adaptation studies for the Polish version of the measure. The permission was granted.

The presented instrument was translated independently by four professionals: two research psychologists and two professional English translators. The translated version was then back translated by the second professional translator to ensure compatibility with the original version. The translations provided by psychologists and professional translators turned out to be consistent.

Data collection procedure

The survey was conducted remotely using the Google Forms service. Before the study commenced, participants were required to confirm their familiarity with the nature of the study and rules of participation, confirm that they had reached the age of majority, and provide their informed consent. Participation was voluntary and did not involve any material benefits.

Statistical analyses

Statistical analyses for the present study were conducted using the Jamovi software package to calculate Pearson's correlation coefficients and reliability coefficients. Additionally, the R (RStudio ver. 2024.12.0+467) software environment was employed to perform confirmatory factor analysis (CFA) and second-order factor analysis. For these analyses, the lavaan and semPlot packages were utilized, as they provide robust tools for structural equation modeling and visualization of the resulting factor structures.

RESULTS

Factor structure of the Blood Donor Planned Behavior Survey in the Polish sample

1.1 Confirmatory factor analysis

A confirmatory factor analysis was performed on the study group (n = 422; χ2=794.937; df = 164; p <.001) using maximum likelihood estimation. The goodness-of-fit indices revealed that the model with four factors was adequately fitted to the data: RMSEA = .095; 95% CI [.089;.102] CFI = .958; TLI = .935; SRMR = .107; AIC = 30952.88.

Figure 1.

Model of confirmatory factor analysis of the measures with correlations and corresponding items with beta weights for the Planned Behavior Measure. Double-headed arrows indicate the correlations between the scales. Single-headed arrows indicate the factor loadings for each item within its scale.

1.2 Second order Confirmatory Factor Analysis

A second-order confirmatory factor analysis (CFA) was conducted on the study group (N = 422) using maximum likelihood estimation. The structural equation modeling (SEM) analysis indicated an acceptable model fit to the data (χ²(177) = 655.42, p < .001; CFI = .93; TLI = .92; RMSEA = .08, 90% CI [.074, .087]; SRMR = .082). The Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) were above the recommended threshold of .90, indicating good model fit. Additionally, the Root Mean Square Error of Approximation (RMSEA) and Standardized Root Mean Square Residual (SRMR) values supported the model’s adequacy. In the model, Intention, the dependent variable, was significantly predicted by Attitude, Subjective Norms, and Perceived Behavioral Control. The regression coefficients demonstrated a negative effect of Attitude (β = -0.216, p = .008), a positive effect of Subjective Norms (β = 0.193, p = .013), and a strong positive effect of Perceived Behavioral Control (β = 0.943, p < .001) on Intention. The model accounted for 61.4% of the variance in Intention (R² = 0.614). The adjusted coefficient of determination (R²) was 0.611, accounting for the number of predictors in the model. The adjusted R² was also calculated. The difference between the unadjusted and adjusted (ΔR² = 0.0028) was minimal, suggesting that the model was not overfitted and that the number of predictors was appropriate given the sample size.

Figure 2.

Model of second order confirmatory factor analysis of the measures with correlations and corresponding items with beta weights for the Planned Behavior Measures and its subscales.

Reliability analysis

In the next step, the internal consistency of the Polish version of the TPB metrics (KTPZHK) was assessed using two indicators – Cronbach's α and McDonald's ω. The reliability coefficients reached acceptable, satisfactory, and high results for each of the scales and subscales. The reliability coefficients of the Polish version are mostly similar to those calculated for the validation of the original tool. Results are shown in Table 1.  

Table 1.

The internal consistency of TPB metrics in the Polish adaptation compared to the original version

Scale/subscale			M	SD	Polish version		Original version
					α	ω	α1	α2
Attitude		Cognitive	5.99	1.46	.88	.88	.82	.86
		Affective	5.23	1.56	.76	.78	.90	.86
		Total	5.61	1.28	.82	.84	.80	.85
Subjective norm		Injuctive	3.34	1.80	.87	.89	.86	.88
		Descriptive	3.07	1.85	.92	.92	.87	.86
		Total	3.35	1.62	.90	.90	.86	.84
Perceived behavioral control		Self-efficacy	3.674	1.76	.75	.77	.91	.87
		Controllability	4.22	2.14	.88	.89	.93	.95
		Total	3.94	1.50	.74	.77	.83	.90
Intention		Total	2.774	2.0	.96	.96	.98	.95

Note. α = Cronbach’s α; ω = McDonald’s ω; α₁ - Ohio University sample; α₂ - NYBC sample

External consistency analysis

3.1 External consistency of the Attitude Measure

The next step was to evaluate the external consistency of the Polish version of the Attitude Measure (see Table 2). To this end, four instruments were used – The Light Triad Scale, The Flourishing Scale (FS), Generalized Self-Efficacy Scale (GSES) and The Revised NEO Personality Inventory (NEO-PI-R).

The correlation analysis revealed positive and statistically significant relationships between Faith in Humanity, Humanism, Kantianism, Flourishing, Self-efficacy, Kindness, Ideas, Altruism, and Attitude, along with its subscales. A noticeably stronger relationship can be observed between Altruism and cognitive Attitude compared to its relationship with affective Attitude. The overall score of the Attitude scale shows the strongest correlation with Self-efficacy.

Table 2.

Pearson’s r correlation coefficients for Light Triad, Flourishing, Self Efficacy, NEO-PI-R subcales and Attitude measure

1

2

3

4

5

6

7

8

9

10

11

12

13

1

Faith in humanity

-

2

Humanism

.47***

-

3

Kantianism

.36***

.51***

-

4

Flourishing

.34***

.34***

.37***

-

5

Self - efficacy

.34***

.30***

.35***

.23***

-

6

Kindness

.40***

.45***

.33***

.43***

.24***

-

7

Feelings

.22***

.35***

.31***

.26***

.10*

.40***

-

8

Actions

.07

.17***

.09*

.15***

.10*

.19***

.20***

-

9

Ideas

.09*

.24***

.18***

.13**

.18***

.21***

.34***

.21***

-

10

Altruism

.38***

.37***

.38***

.39***

.24***

.58***

.37***

.15***

.23***

-

11

Attitude_cognitive

.22***

.24***

.32***

.19***

.42***

.13**

.19***

.08

.11**

.21***

-

12

Attitude_affective

.18***

.15**

.16***

.14**

.50***

.12**

.08

.05

.02

.12**

.45***

-

13

Attitude

.23***

.23***

.28***

.19***

.54***

.15**

.16***

.08

.08

.19***

.84***

.86***

-

Note. * p < .05, ** p < .01, *** p < .001

3.2 External consistency of the Subjective Norm Measure

The next step was to evaluate the external consistency of the Polish version of the Subjective Norm Measure (see Table 3). To this end, three instruments were used – The Light Triad Scale, The Revised NEO Personality Inventory (NEO-PI-R) and the Gratitude Questionnaire (GQ-6).

The correlation analysis revealed positive and statistically significant relationships between Faith in Humanity, Kindness, Ideas, Altruism and injunctive norms. Next, statistically significant relationships were observed between Faith in Humanity, Kindness, Actions, Ideas, Altruism, and descriptive norms. The overall Subjective Norms scale correlated positively and significantly with Faith in Humanity, Humanism, Kantianism, Kindness, Feelings, Ideas, Altruism, and Gratitude.

Table 3.

Pearson’s r correlation coefficients for Light Triad, NEO-PI-R, Gratitude and Subjective Norms measure.