The role of teacher professional capital in developing distributed leadership: evidence from a centralized system

BackgroundEffective leadership in clinical nursing education is crucial for shaping competent practitioners and ensuring quality patient care. Despite its importance, there is no psychometrically validated instrument specifically designed to assess leadership styles in this context. This study aimed to develop and validate the Clinical Leadership Style Scale (CLSS), a tool for measuring leadership styles in clinical nursing education.MethodsA sequential exploratory mixed-methods design was employed with Iranian participants in three phases. Initial item generation was informed by a systematic review (25 articles, 1974–2024) and qualitative content analysis of interviews with 11 stakeholders (faculty, students, administrators). An initial pool of 57 items was created based on these findings and a review of 30 existing instruments. The scale was refined and validated with 522 nursing students through face validity, content validity (CVR > 0.56, κ > 0.75), item analysis (α = 0.87), exploratory factor analysis (KMO = 0.943), and confirmatory factor analysis (CFI = 0.97, RMSEA = 0.094).ResultsThe final 35-item CLSS measures three leadership styles: Dynamic Leadership (α = 0.96), Dysfunctional Authoritative Leadership (α = 0.93), and Systematic-Static Leadership (α = 0.78). The scale demonstrated strong internal consistency (α/Ω = 0.78–0.97), test-retest reliability (ICC = 0.88–0.92), and discriminant validity (HTMT < 0.37). A negative correlation was observed between Dynamic and Dysfunctional Authoritative styles (r = − 0.72), and a positive correlation between Dynamic and Systematic-Static styles (r = 0.58).ConclusionThe CLSS is a reliable and valid instrument for evaluating leadership styles in clinical nursing education. It can support faculty development, promote positive leadership behaviors, and enhance educational outcomes.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12912-025-03694-6.

(1) Background: The last few decades have seen researchers giving considerable attention to the physical context of early childhood care and development (ECCD) centers because many of the underlying processes that link physical context are quite similar to psychosocial environmental factors regarding child development. However, research on the physical environments, and the employees’ understanding of the importance of physical environments, is often underestimated. The purpose of this study was to assess the quality of the physical environments of ECCD centers in the Cape Coast Metropolis, Ghana, and ascertain whether being a private or public center (center auspices) would be associated with the quality of its physical environment. A further inquiry into the educators’ understanding of the importance of physical environment on children’s developmental outcomes was made. (2) Methods: Using a sequential explanatory mixed-methods research design, all 160 ECCD centers in the Cape Coast Metropolis were assessed using a modified version of the Children’s Physical Environment Rating Scale (CPERS) and a semi-structured interview guide. (3) Results: Descriptive statistics indicated that more than half of the ECCD centers, 56%, rated “fair” on the quality of their physical environment. Although the locations and sites of these centers were of good quality, other physical environmental characteristics (i.e., “Planning of the Centre”, “Building as a Whole” and “Outdoor Space”) of ECCD centers were also rated to be fair. A Chi-square test showed that center auspices (i.e., being private or public) were not significantly associated with the quality of the physical environments of the centers [χ2(2) = 2.490, p > 0.05], suggesting no significant difference between private and public ECCD centers in terms of the quality of their physical environment. A follow-up qualitative inquiry identified two themes as reasons why play yards in early years’ schools were not good: a ‘‘lack of funding” and “governmental support”. (4) Conclusions: Our findings suggest that the physical environments of ECCD centers are, to some extent, compromised. Stakeholders (e.g., Ghana Education Service, non-governmental/religious organizations, and private entrepreneurs) should help improve the quality of physical environments and also provide financial assistance for the provision of basic equipment (e.g., learning materials) for private and public ECCD centers in the Cape Coast Metropolis. Educators require in-service training to boost their in-depth understanding of the importance of physical environments on children’s developmental outcomes. Future studies could target children’s perceptions of their preschools’ physical environments as useful empirical information to help guide appropriate policy interventions.

Sequential explanatory mixed method design is the most frequently applied in both health and social sciences literature. It is denoted by ‘QUAN → qual’ which represents the quantitative study occurs first and has greater weight in addressing the study’s aims, and the qualitative study follows to explain quantitative results. Despite the extensive use of sequential explanatory design, there are limited references to this design. Therefore, this methodological paper attempts to fill the gap by providing an illustration in developing a sequential explanatory interview schedule based on complementary-alternative medicine (CAM) study among clinical psychologists in Indonesia. The most important step to develop sequential explanatory interview schedule was the construction of aspects and questions that were immensely grounded on the most notable quantitative results. In this study, eight aspects of interview schedule were constructed after analyses of the nationwide survey. The interview schedule then piloted among participants with fairly similar characteristics to the participants in the main interviews. This process enhanced the quality of questions through feedback from participants and improved the interviewer’s skills through familiarization with questions. It is expected that this reflection report could be adopted as a practical guideline in developing interview schedule for sequential explanatory mixed method design, particularly in the field of psychology.

The importance of teacher performance in improving achievement to determine the quality of education and school performance, This study is an Exploratory Sequential mixed method design study. aims to influence leadership, work motivation, and organizational culture on teacher performance and achievement, both partially and simultaneously with Exploratory Sequential Design . This approach combines qualitative and quantitative methods, starting with an in-depth exploration of the factors that influence the effectiveness of teacher work performance, followed by testing the quantitative model. This research was conducted at SMP Negeri 3 Numfor Barat in a remote area. To achieve the objectives of this study, the researcher applied Exploratory Sequential mixed method design research with a case study approach . In the qualitative stage, the research data was collected through observation, in-depth interviews with 1 head of educational unit and 10 subject teachers, and document analysis to identify needs, challenges, and best practices in management. The research data was processed through the stages of data collection, data presentation, data reduction, and data conclusion drawing. To ensure the validity of the research data, the researcher conducted data confirmation and credibility by involving the Education Office for the development of educational resources and school supervisors. The results of the study indicate that: (1) the teacher training management model in improving work performance that has been implemented in remote areas consists of the planning, organizing, implementing and evaluating stages. (2) The function of the teacher training management model in improving work performance that has been implemented in remote areas runs effectively and efficiently. The results of this study provide important information for the government, school supervisors, principals and teachers. leadership, work motivation, and organizational culture simultaneously have a positive and significant effect on teacher work performance.

Transformative sequential mixed methods design in a cross-cultural context is seldom straightforward. Using a community-based participatory research approach as the transformative lens in an African refugee context in the southern United Status, we explored: (a) the intersection of culture, financial stress, and financial self-efficacy and (b) tested the efficacy of financial literacy as the focus of a culturally responsive solution grounded in community-identified priorities. Through a three-phased explanatory sequential mixed methods design, we demonstrate how the addition of a third phase of analysis that focuses on convergence and expansion of quantitative and qualitative data integration and cyclical processes of dissemination and action can strengthen the utility of transformative mixed methods research in a cross-cultural context. Our study offers a unique contribution to the long-standing methodological dialogue between the design elements of mixed methods research, community-based participatory research, and migration studies by expanding the transformative explanatory sequential design archetype in a cross-cultural context.

Prenatal care is vital for ensuring healthy pregnancies, yet many women face barriers such as geographic distance, socioeconomic limitations, and lack of transportation. Mobile health (mHealth) technologies offer a promising approach to improving access to prenatal care information. However, the motivations, barriers, and behaviors related to mHealth app use, particularly within diverse cultural and sociodemographic contexts, remain underexplored. This study aimed to investigate Iranian pregnant women's intention to use mobile health apps and identify its determinants using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. A sequential exploratory mixed-methods design was employed, comprising qualitative content analysis followed by a quantitative survey. In the qualitative phase, semi-structured interviews were conducted with 14 pregnant women and 7 healthcare professionals, guided by the UTAUT model. Directed content analysis was used to explore participants' experiences and perceptions. In the quantitative phase, a cross-sectional survey based on the UTAUT framework was administered to 60 pregnant women. Inclusion criteria included being currently pregnant, having access to a smartphone, and using an mHealth app for prenatal care. Participants were recruited via email and social media platforms. Data were analyzed using SPSS version 29. A concurrent triangulation approach was used to integrate qualitative and quantitative findings. Qualitative findings indicated that performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) shaped behavioral intentions to use mHealth apps. Participants appreciated features such as appointment reminders and symptom trackers, but also raised concerns regarding information accuracy and app usability. Social influences from peers and healthcare providers were especially influential. Quantitative results confirmed that PE (B = 0.47, p < .001), EE (B = 0.35, p = .009), and SI (B = 0.28, p = .049) were significant predictors of behavioral intention to use mHealth apps. FC (B = 0.23, p = .131), however, did not have a statistically significant direct effect. The integration of qualitative and quantitative findings offers a comprehensive understanding of the factors influencing pregnant women's behavioral intentions to use mHealth apps. To enhance adoption and effectiveness, mHealth app design should prioritize usability, credibility, and support mechanisms tailored to prenatal care needs.

BackgroundReablement is a multi-professional and internationally established home-based health care service for mainly older people with the aim to reduce the need for long-term care and to promote self-determination. However, it is unknown which factors would facilitate the implementation of reablement in health care services. Therefore, the aim of this work was to identify relevant factors for the implementation process and to elucidate their importance based on the perspectives of experts.MethodsWithin an exploratory sequential mixed-methods design, a literature search followed by framework analysis was carried out using the five domains of the Consolidated Framework of Implementation Research (CFIR) to collect potentially relevant factors for implementation of reablement. A survey was then drawn up encompassing the factors identified. Within the survey international reablement – experts were asked to rate the relevance of these factors .ResultsThe literature search identified 58 publications that served as sources for the framework analysis, where 40 potentially relevant factors were clustered into the five CFIR domains. These 40 factors were rated by experts in an online-survey. Based on the analysis of survey-data, 35 factors were considered as relevant for implementation of reablement services. The CFIR-domain characteristics of individuals, including teamwork and communication skills, was seen as most relevant.ConclusionsThe implementation of reablement services is complex and requires the consideration of numerous factors, especially regarding the CFIR-domain characteristics of individuals. From the perspective of the survey´s participants one important factor of a successful implementation was the engagement of the persons involved. It requires team members with a strong, shared vision. Communication skills are highly important to promote teamwork and intensive training is needed to establish these skills. Further research on the implementation of reablement services is essential to realize its full potential.

Leadership stems from recognition and acceptance, surpassing the mere reliance on their title. Research indicates varying perceptions of relationship values between leaders and followers. A leader’s crucial awareness of these differences prevents harm to the institution through disagreements that expose poor style and self-knowledge. This study examines the perception difference of deans’ leadership styles in Maldives higher education institutes using self-rating and their lecturers’ perceptions using followers rating. In this study, a sequential explanatory mixed-method design was used. The first phase collected data via surveys from deans and lecturers (N = 190) from nine different HEI, with SPSS used for analysis. The second phase included qualitative interviews with deans and lecturers (N = 21), which were evaluated using template analysis. The independent sample t-test was used to assess the difference in averages between two independent groups, leaders and lecturers. According to the data, there was a slight statistically significant difference between deans’ self-assessments of their own current leadership styles and lecturers’ ratings of their leaders’ existing leadership styles. On the other side, it was discovered that both leaders and lecturers like the same leadership approaches. The findings of this research study suggest institutes to focus on developing academic deans’ leadership styles based on followers’ perception. Leadership measurement should consider both leaders’ and subordinates’ perceptions to avoid flawed conclusions. Also, this study calls for academic deans to reflect on their leadership, acknowledge limitations, and engage in developmental activities for growth.

From the last few decades, math anxiety has become the major concern of educationists. Students’ academic achievement especially in mathematics has been considered as a crucial factor in determining the future progress of students. But unfortunately, the participation rate of students in mathematics is decreasing day by day. The main objectives of the study were to assess secondary school students’ anxiety in mathematics and to explore the causes of students’ anxiety in mathematics. A sequential explanatory mixed method research design was used. The data was collected through both quantitative and qualitative methods. A five-point rating scale questionnaire was developed for quantitative data collection. The tool was validated through pilot testing. 100 students participated in pilot testing. Internal consistency of the instrument was assessed by Croanbach’s alpha which was 0.7. The targeted population of the study was both male and female secondary school students from the district Bahawalpur, Punjab. Out of the whole population, 726 male and female students were approached via multi-stage sampling technique. After quantitative data collection data was entered in SPSS version 20 and percentage, frequency distribution and mean score was calculated. Based on the quantitative data results it was observed that secondary school students were numerophobic and had moderately a high level of anxiety in mathematics. On the basis of quantitative results, interviews of secondary school teachers were conducted to explore the causes of students’ anxiety in mathematics. 20 teachers were approached via purposive sampling. The qualitative data revealed that major causes of students’ anxiety in mathematics were lack of practice, lack of previous knowledge, communication gap between student and teacher, and lack of interest in mathematics.

The aim of this study is to ascertain the problems social studies teachers face in the teaching of topics covered in 8th grade TRHRK Course. The study was conducted in line with explanatory sequential mixed method design, which is one of the mixed research method, was used. The study involves three phases. In the first step, exploratory process was followed, in the second step measurement tool was developed and in the third step the measurement tool was applied to the sample chosen from the universe. In this study, data collection process was realized in two steps. In the first step, qualitative data were collected and later on quantitative data were collected using quantitative measurement tool, which was developed based on qualitative data and then validated. The qualitative study group of the research was determined using criterion sampling, which is one of the purposeful sampling methods. The quantitative study group was determined via double (two-phase) cluster sampling method. In line with the responds provided by the participants, qualitative findings were categorized and presented as 3 themes: (i) inadequacy of course time and the problems caused by intensive content, (ii) adoption of Behaviorist Approach as opposed to constructivism, (iii) Problems caused by perception, attitude towards the course and other factors. Following from this, 23-item quantitative measurement tool was developed and administrated on the qualitative sample of the study composed of 1090 social studies teachers working in 28 cities. Quantitative data indicated that qualitative data can be generalized. As a result, even if the education program of TRHRK is designed according to constructivist approach, traditional, teacher-centered history education based on memorization is continued because of the obstacles defined in the current study.

Objectives: This study investigates the role of school leadership in enhancing institutional performance by exploring the experiences and practices of headteachers in government secondary schools across Punjab, Pakistan. The researchers have focused on transformational, instructional, and distributed leadership theories. Methods: An explanatory sequential mixed-methods design has been adopted to analyze that how these leadership models influence school performance indicators, including student achievement, teacher attendance, retention rates, and community involvement. Quantitative data were collected from a stratified random sample of 300 headteachers using validated instruments. However, qualitative insights were gained through in-depth interviews with 12 purposively selected participants. Findings: Results of the study revealed moderately high implementation of leadership practices, with distributed leadership emerging as the most influential predictor of institutional performance (β = .35, p &lt; .001). Pearson correlations showed significant relationships between all leadership styles and performance, while hierarchical regression and mediation analysis confirmed that distributed leadership partially mediated the effect of transformational leadership on performance. Qualitative findings further contextualized the quantitative results, revealing adaptive strategies such as community engagement, resource mobilization, and shared decision-making in response to bureaucratic and infrastructural constraints. Conclusion: The study concludes that effective school leadership particularly when grounded in distributed practices plays a pivotal role in enhancing institutional outcomes in low-resource contexts like Punjab. These findings offer significant implications for educational policy, leadership training, and school improvement planning. Implications: The research advocates for embedding distributed leadership competencies in professional development programs and aligning school leadership evaluations with data-informed and collaborative practices. Limitations and avenues for future research are discussed, including the need for longitudinal and multi-stakeholder studies to establish causal links and further validate the proposed leadership-performance framework.

BackgroundApathy in patients with epilepsy is associated with a wide range of consequences that reduce the patient’s ability to perform social functions and participate in self-care and rehabilitation programs. Therefore, apathy is one of the important diagnoses of the healthcare team in the process of caring for epileptic patients and its dimensions need to be examined and recognized. Therefore, appropriate instruments with the sociocultural milieu of each community should be provided to health care providers. The aim of the present study was to design and measure epilepsy–related apathy scale (E-RAS) in adults with epilepsy.MethodsThis study of sequential exploratory mixed methods design was conducted in Iran from April 2019 to December 2019. In the Item generation stage, two inductive (face-to-face and semi-structured interviews with 17 adult epileptic patients) and deductive (literature review) were used. In item reduction, integration of qualitative and literature reviews and scale evaluation were accomplished. For Scale Evaluation, face, content, construct [exploratory factor analysis (EFA) (n = 360) and confirmatory factor analysis (CFA) (n = 200)], convergent and divergent Validity and reliability (internal consistency and stability) were investigated.ResultsThe results of EFA showed that E-RAS has four factors, namely, motivation; self-regulatory; cognition and emotional-effective. These four latent factors accounted for a total of 48.351% of the total variance in the E-RAS construct. The results of CFA showed that the 4-factor model of E-RAS has the highest fit with the data. The results of convergent and divergent validity showed that the values of composite reliability (CR) and average variance extracted (AVE) for the four factors were greater than 0.7 and 0.5, respectively, and the value of AVE for each factor was greater than CR. The Cronbach’s alpha coefficient for the whole scale was obtained 0.815. The results of the test-retest showed that there was a significant agreement between the test and retest scores (P < 0.001).ConclusionE-RAS is a multidimensional construct consisting of 24 items, and has acceptable validity and reliability for the study of epilepsy-related apathy in adult epileptic patients.

This study aimed to determine the effect of Outdoor Learning Inquiry-Based Activities (OLIBA) on the performance of grade 5 students in science. A sequential explanatory mixed methods design was used in the study. The respondents were the 180 grade 5 students from the representative divisions in Region XI. Sixty (60) grade 5 students from each division namely Davao Occidental, Tagum City, and Davao City were considered as respondents. The study utilized two instruments; the standardized test and the researcher-developed interview guide. The statistical tools employed were Mean and standard deviation and Independent Samples t-test. The results revealed the pretest performance of the students in the experimental and control groups in the three divisions was described as fairly satisfactory. Also, the students in the experimental group demonstrated an outstanding performance in the posttest due to the use of OLIBA while the control group registered a very satisfactory performance with the use of the traditional style of teaching. The result of qualitative analysis of participant's experiences in the pretest revealed similarities in content difficulty. After the implementation of OLIBA, both pupils and teachers revealed similarities in knowledge acquired and engagement due to OLIBA. Keywords: Inquiry-based; learners; outdoor learning; performance; sequential explanatory

Inpatients commonly experience problems with elimination due to incontinence, urinary retentions, and complications with indwelling catheters. Although elimination care (EC) is an important nursing area, few studies explore the burden of EC on nurses. To identify the burden on EC by analyzing nurses' opinions using sequential explanatory mixed method. This research was conducted using a sequential explanatory mixed-methods design. A total of 59 nurses at a tertiary hospital in South Korea participated in the study from January 1 to March 31, 2022. For quantitative analysis, information about number of delays of work due to EC, required time for serving bedpan or diaper changes, percentage of EC per shift, and percentage of patients who need EC was collected through a survey. For qualitative analysis, focus group interviews were conducted to identify factors that put a burden on EC. Important themes were derived by analyzing nurses' opinions on EC. For nurses in intensive care units, general wards, and integrated nursing care wards, the number of work delays due to EC was 3.6 ± 1.5, 2.3 ± 1.2, and 4.8 ± 2.4 (p<0.01), respectively. The mean percentage of EC work out of total nursing tasks per shift was 36.2 ± 19.0, 29.3 ± 14.4, and 43.8 ± 14.1 (p=0.02), respectively. The mean percentage of patients requiring EC out of patients a nurse cares was 85.4 ± 16.6, 41.3 ± 26.1, and 58.8 ± 21.9 (p<0.01), respectively. Following qualitative analysis, four themes related to nurses' EC burden were derived: physical burden, frequent care needs, delay of other jobs due to EC, and complications. Among them, frequent care needs were found to be the primary factor requiring consideration to reduce nurses' burden. This research found that EC is one of the most burdensome tasks that nurses want to avoid. To alleviate their burden, effective EC protocol or smart medical devices assisting with EC should be developed.

Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3) integration and discussion of results. Furthermore, we illustrated the application of this framework by examining the relationships between learning process metrics and academic performance in the subject of Computer Programming coupled with content analysis of the responses to a students’ perception questionnaire of their learning experiences in this subject. Background: There is a prevalence of quantitative research designs in learning analytics, which limits the understanding of students’ learning processes. This is due to the abundance and ease of collection of quantitative data in virtual environments and learning management systems compared to qualitative data. Methodology: This study uses a mixed-methods, non-experimental, research design. The quantitative phase of the framework aims to analyze the data to identify behaviors, trends, and relationships between measures using correlation or regression analysis. On the other hand, the qualitative phase of the framework focuses on conducting a content analysis of the qualitative data. This framework was applied to historical quantitative and qualitative data from students’ use of an automated feedback and evaluation platform for programming exercises in a programming course at the National University of Colombia during 2019 and 2020. The research question of this study is: How can mixed-methods research applied to learning analytics generate a better understanding of the relationships between the variables generated throughout the learning process and the academic performance of students in the subject of Computer Programming? Contribution: The main contribution of this work is the proposal of a mixed-methods learning analytics framework applicable to computer programming courses, which allows for complementing, corroborating, or refuting quantitatively evidenced results with qualitative data and generating hypotheses about possible causes or explanations for student behavior. In addition, the results provide a better understanding of the learning processes in the Computer Programming course at the National University of Colombia. Findings: A framework based on sequential explanatory mixed-methods design in the field of learning analytics has been proposed to improve the models used to support the success of the learning process and the learner. The answer to the research question posed corresponds to that the mixed methods effectively complement quantitative and qualitative data. From the analysis of the data of the application of the framework, it appears that the qualitative data, representing the perceptions of the students, generally supported and extended the quantitative data. The consistency between the two phases allowed us to generate hypotheses about the possible causes of student behavior and provide a better understanding of the learning processes in the course. Recommendations for Practitioners: We suggest implementing the proposed mixed-methods learning analytics framework in various educational contexts and populations. By doing so, practitioners can gather more diverse data and insights, which can lead to a better understanding of learning processes in different settings and with different groups of learners. Recommendation for Researchers: Researchers can use the proposed approach in their learning analytics projects, usually based exclusively on quantitative data analysis, to complement their results, find explanations for their students’ behaviors, and understand learning processes in depth thanks to the information provided by the complementary analysis of qualitative data. Impact on Society: The prevalence of exclusively quantitative research designs in learning analytics can limit our understanding of students’ learning processes. Instead, the mixed-methods approach we propose suggests a more comprehensive approach to learning analytics that includes qualitative data, which can provide deeper insight into students’ learning experiences and processes. Ultimately, this can lead to more effective interventions and improvements in teaching and learning practices. Future Research: Potential lines of research to continue the work on mixed-method learning analytics methodology include the following: first, implementing the framework on a different population sample, such as students from other universities or other knowledge areas; second, using techniques to correct unbalanced data sets in learning analytics studies; third, analyzing student interactions with the automated grading platform and their academic activities in relation with their activity grades; last, using the findings to design interventions that positively impact academic performance and evaluating the impact statistically through experimental study designs. In the context of introductory programming education, AI/large language models have the potential to revolutionize teaching by enhancing the learning experience, providing personalized support, and enabling more efficient assessment and feedback mechanisms. Future research in this area is to implement the proposed framework on data from an introductory programming course using these models.