Impact of emotional intelligence and conflict management on workplace dynamics in Hossana Health Centers, Central Ethiopia

Abstract

Background

Emotional intelligence (EI), conflict management (CM), and performance effectiveness (WPE) are emerging areas of study in workplace dynamics in healthcare. Rural health centers in Ethiopia lack documented studies on these areas. This study aimed to analyze the correlation between emotional intelligence, conflict management, and workplace performance effectiveness among healthcare workers in Hossana Town, Central Ethiopia.

Methods

This study used a mixed-methods research design with the dominant quantitative research approach. Three public health centers provided 213 participants. Data was collected using self-administered questionnaires. Emotional intelligence was measured by the Schutte Self-Report Emotional Intelligence Test (SSEIT); conflict management was measured by a validated Conflict Management Scale; and workplace performance effectiveness was measured using a 7-item scale, WPE (7 to 35). Data was analyzed using SPSS version 25. Participants’ scores of emotional intelligence, conflict management, and workplace performance effectiveness had a Cronbach’s alpha of 0.87, 0.84, and 0.88, respectively. Quantitative data were supplemented by 12 health care managers’ semi-structured interviews, and the data were analyzed thematically.

Results

Participants indicated above-average emotional intelligence (M = 40.17; SD = 6.237) and high conflict management (M = 40.23; SD = 6.609). EI and CM had a strong (r = 0.791; p < 0.01) positive relationship. Regression analysis indicated that both EI and CM jointly explained 58.5% of the variance of WPE (R2 = 0.585; p < 0.001; F(2,210) = 159.087). The direction of the impact indicated that CM (β = 0.455; t = 6.397, p < 0.001) had a stronger predicting effect when compared to EI (β = 0.303; t = 4.255, p < 0.001). The qualitative interviews identified four themes: (1) increased emotional awareness lessens everyday disputes, (2) a major absence of training for formal dispute management, (3) highly demanding workloads coupled with scarce resources create a heightened level of interpersonal friction, and (4) managers use informal, relationship-based methods. These qualitative themes explain the quantitative data by showing the contradiction of high self-reported CM scores with no training.

Conclusion

In rural Ethiopian health centers, the EI and CM of health care workers help predict job performance effectiveness. Managers use EI intuitively to resolve disputes, but there is no CM training. Health care policymakers need to provide EI and CM training in professional development for health workers in resource-limited settings.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s40359-026-05108-x.

Introduction

Background of the Study

Healthcare workplaces need their employees to have excellent control over their emotions and relationships. The combination of Guleman’s [27] self-regulation, self-awareness, and social skills, as well as Alhazri and Bugis’s [1] empathy and social skills, is critical to maximizing job-related social skills and work-related social skills [2, 13, 17, 33]. CM [3] is the ability to deal with work-related social skills [13]. Performance-related social skills of employees of various companies are positively related to the following: proactive personality [7], EI, transformational leadership, and job satisfaction [34].

Due to the limited resources and stretched workforce, and ongoing conflicts, EI and CM are vital to improving the work and job satisfaction of employees in the Ethiopian health industry [14]. It is reported by the Hossana Town Administration (2023) that public health facilities serve a considerably bigger community than their designed health services, which produces a permanently stressful work environment for health care staff [43]. It is thought that persons with higher levels of EI are more likely to be satisfied with their work, and that is related to the collaboration established by the constructive settlements of the interpersonal disputes [20, 38]. Furthermore, high-involvement work practices and job crafting have a beneficial effect on innovative behaviors in nurses, demonstrating that workplace innovation is determined by emotional and psychological resources [4, 22].

Research Gap: Much of the research on EI and CM has been concentrated on the developed healthcare systems. However, they are generally lacking for the Ethiopian primary health centers. On the African continent, the combined effect of EI and CM on work performance in healthcare systems has been examined in very few studies. This work seeks to address this gap.

Statement of the problem

The plurality of staff shortage problems in Ethiopian healthcare creates conditions where there is more work for fewer staff. There is also a problem with the conflicts between coworkers, employees, and supervisors [25, 32]. According to Bekalu et al. [15], the primary source of dissatisfaction for nurses in Ethiopia’s public hospitals is workplace conflicts. [45] stated that the level of satisfaction of nurses in Ethiopia is lower relative to that of nurses in the neighboring countries. [35] argued that workplace conflicts and the provision of emotional support have an effect on the performance of nurses as well as their willingness to stay in the organization. Emotional intelligence (EI) has been shown to reduce turnover intention in other contexts [8] by mediating the relationship between job satisfaction and turnover intention.

Despite the potential of EI and CM to remove barriers to retention caused by workplace stress within the Ethiopian healthcare system, their use in the education and administrative systems is wanting [49]. Ethiopia also lacks research on EI and CM in the health centers.

Objectives of the study

General objective

The overall objective was to assess the association between emotional intelligence, conflict management, and workplace dynamics in health centers in Hossana Town, Central Ethiopia.

Specific objectives

1. To assess the level of emotional intelligence (self-awareness, self-management, social awareness, relationship management) among health workers.

2. To examine the association between conflict management skills and job satisfaction levels.

3. To determine the predictive power of emotional intelligence and conflict management on workplace performance effectiveness.

Significance of the study

Findings may guide healthcare administrators in justifying investment in non-technical skills training to minimize tensions and improve collaboration.

Scope of the study

The study focused on three public health centers in Hossana Town, examining how EI and CM influence work performance, relationships, and the overall environment among clinical and non-clinical staff.

Literature review

Emotional intelligence and conflict management in healthcare

High EI is associated with empathy, listening skills, and stress management and likely performs better at work as identified by several studies [16, 29]. Conflict management styles range from avoidance all the way to cooperation, as explained by [39]. Collaborative strategies are most useful in the healthcare profession, as they help develop imaginative, mutually beneficial solutions [19]. EI improves resolution of conflicts [44]. Effective conflict management improves job satisfaction, teamwork, and patient care [31]. Conflict brings about absenteeism and turnover and even increases medical errors [3].

Evidence from Ethiopia: According to [32] inadequate resources, lack of supervision, and unprofessional attitude, with competing priorities, are the main causes of workplace conflicts. Managers are bound to conflict. They react by confronting, blaming, and committing to work. [25] showed that job satisfaction brought better coworker relationships. Effective organizational policy, better training, and a salary are beneficial for employee satisfaction. Negative attitudes toward service lead to a lack of teamwork and failure to engage in collaborative work.

International Evidence: Alwali [4] said that the creativity of the nursing staff is related to transformational leadership and a clear distribution of roles. In addition, [6] states that the presence of more inclusive leadership creates an empowered and more creative workforce. Moreover, [9] state that the integration of AI-enhanced HRM and EI can transform leadership and teamwork. [9] also state that the combination of AI-enhanced HRM and EI affects leadership and teamwork.

Components of emotional intelligence

According to Salovey and Mayer [42], EI entails the ability to understand and manage one’s own and others’ emotions. [27, 28] develops a five-factor model of EI, which includes self-regulation and self-control and extends to social skills and empathy.

In the field of healthcare, [26] state that employees with high EI can remain relaxed and less stressed at work. EI is associated with a positive attitude and improved job satisfaction [7, 8]. The work of [28] states that self-control encourages calmness and the maintenance of appropriate work behavior. EI may promote equity and justice in healthcare by the removal of some of the barriers to health [36].

Conflict management styles in the workplace

In the model established by [47] assertiveness and cooperativeness (c1-2) define five styles. In the healthcare sector, collaboration is essential. EI is associated with constructive conflict resolution and improves the quality of patient care and cooperation overall [46].

Conceptual framework

The model that is suggested predicts the effect of the work functions’ effective performance (dependent variable) based on the interaction between EI and CM (independent variables). The model involves EI, CM, WPE, work satisfaction, perceived work productivity, teamwork quality, work-related stress, and other variables.

The framework also acknowledges the relationship between EI and CM. The Job Demands-Resources (JD-R) model [11, 12] offers the theory. EI and CM are personal resources that aid healthcare workers in managing the demands of their job (the large number of patients and the limited resources) and help sustain their performance (Fig. 1).

Fig. 1.

Conceptual Framework

Materials and Methods

Study area and period

The study was conducted in Hossana Town, Central Ethiopia, from July 2023 to March 2024. Hossana, the capital of the Hadiya Zone, has three public health centers (Hossana, Lichamba, and Bobicho) that provide primary healthcare services to approximately 120,000 residents. During the study period, 452 healthcare workers were employed across these facilities.

Study design

Quantitative-dominant mixed-methods design: cross-sectional survey (N = 213 after cleaning) followed by semi-structured interviews with 12 managers to contextualize findings.

Population and sampling technique

Source Population: All employees working in Hossana Town's government health centers.

Study Population: Staff who met inclusion criteria and were selected for sampling.

Inclusion Criteria:

• Employed at one of the three public health centers in Hossana Town

• Minimum six months of work experience at the facility

• Employed at least 20 h per week

• Willing to provide informed consent

Exclusion Criteria:

• Employees working outside government health centers

• Employees with less than six months of experience

• Staff on annual or sick leave during the data collection period

• Administrative staff without direct patient contact

Sample Size Calculation: A single population proportion formula was employed [21]:

n = (z2 × p × (1-p))/d2.

Where:

z = 1.96 (95% confidence level).

p = 0.50 (estimated proportion, as no published studies exist for this setting).

d = 0.05 (margin of error).

This yielded n = 384. Since the total source population was 452 (less than 10,000), a correction formula was applied:

A 10% contingency for non-response was added: 208 + (10% × 208) = 229 participants.

Sample Size Justification for Regression Analysis: To be sure that there is enough power for the main inferential analysis, I have performed an additional power analysis by means of G Power (Version 3.1.9.7) [23]. With α = 0.05, power = 0.80, a medium effect size (f2 = 0.15), and five predictors, we found that the minimum required sample size was 92. After data cleaning, the final sample (N = 213) exceeded this, confirming sufficient power for the regression model.

Sampling Procedure: A stratified random sampling technique was used. Strata were defined by the health center:

• Hossana Health Center (n = 185 staff) → 94 participants selected

• Lichamba Health Center (n = 135 staff) → 68 participants selected

• Bobicho Health Center (n = 132 staff) → 67 participants selected

Within each stratum, participants were selected using simple random sampling from the staff roster provided by each health center administration.

Data collection tools

Emotional Intelligence Measurement: The researcher employed the short form of the Schutte Self-Report Emotional Intelligence Test (SSEIT-SF), which includes ten items (Schutte et al., 1998; see also [10] for validation). Each item was scored on a five-point Likert scale, which ranges from 1 (Strongly Disagree) to 5 (Strongly Agree). Responses include "I know my emotions when I feel them," "I can tell how others feel," or "It is easy for me to control my emotions." "The total score range is 10–50, and a high score indicates a high level of EI. In our study, the SSEIT-SF has shown excellent internal consistency (Cronbach's alpha = 0.87).

Conflict Management Measurement: The researcher used a ten-item scale based on the Thomas-Kilmann Conflict Mode Instrument (TKI) [47]. Copyright permission to use and adapt the TKI was granted by CPP Inc. This tool assesses the five different styles of managing conflicts: competing, collaborating, compromising, avoiding, and accommodating. There are two items per style. Respondents have to choose one response among five choices, representing a Likert scale with values ranging from 1 (never) to 5 (always). The total scores range from 10 to 50, and higher scores reflect better conflict management. This scale also has an acceptable reliability (Cronbach's alpha = 0.84).

Workplace Performance Effectiveness Measurement: WPE was measured through a 7-item scale designed for this study and grounded on a literature review [24, 41]. The scale measured the following: (1) job satisfaction (2 items), (2) perceived productivity (2 items), (3) quality of teamwork (2 items), and (4) stress management (1 item). Items were rated on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). Three experts in healthcare management validated the content of the items. The scale demonstrated excellent reliability as evidenced by a Cronbach’s α of 0.88 for the present study.

Demographic Variables: Age, gender, education level, job role (clinical/non-clinical), and years of experience were collected.

Translation Procedure: The bilingual researcher translated the questionnaires from English to Amharic. Then, a pilot test of the Amharic versions was conducted on 30 healthcare workers (not included in the main survey) to confirm the clarity, comprehension, and cultural relevance of the questions. No significant issues were identified. After the pilot test, the researcher translated the Amharic versions back into English to verify that the meaning had not been altered.

Data collection procedures

Self-administered questionnaires during breaks/shifts (Oct 2023–Jan 2024). Response rate: 100% of distributed. Interviews (25–45 min) audio-recorded, transcribed verbatim.

Data analysis techniques

The version of SPSS 25 was used for the descriptive analysis of the collected quantitative data. To illustrate the sample description and the distribution of EI, CM, and WPE, descriptive stats were employed to compute means, standard deviations, frequencies, and percentages of each descriptive stat.

Bivariate analysis using the Pearson product-moment correlation examined the relationship between emotional intelligence and conflict management. Multiple linear regression analysis evaluated emotional intelligence and conflict management as predictors of workplace performance effectiveness. Before regression analysis, the following assumptions were evaluated and verified: Linearity (assessed using scatterplots), normality of residuals (Shapiro–Wilk and Q-Q plots), homoscedasticity (standardized residuals vs. predicted values), and independence of errors (assessed using the Durbin-Watson statistic). Multicollinearity was evaluated using the Variance Inflation Factor (VIF) and tolerance statistics. A VIF value of less than 5 and a tolerance of greater than 0.20 were considered satisfactory. The alpha level of 0.05 was used to evaluate all other tests.

Qualitative data collection and analysis

After the quantitative survey, semi-structured interviews were conducted with 12 healthcare managers (4 from each of the three health centers). Of those who completed the survey and volunteered for follow-up, participants were purposively sampled. Questions were developed to cover (1) experiences of conflicts at work, (2) the role emotional intelligence plays in day-to-day management, (3) current methods of conflict resolution, and (4) challenges to successful conflict resolution. Each interview was conducted in a private room in each health center, was 25 to 45 min in length, and was digitally recorded and transcribed.

The researcher evaluated the interview data using thematic analysis based on the six-phase framework of [18]. To establish dependability, two independent coders first coded three transcripts. This approach resulted in a Cohen's κ of 0.84, which suggests strong agreement between the coders. Whenever there were conflicts, the researcher talked them over to resolve the issue. Subsequently, themes were developed and reviewed for consistency across all transcripts.

Ethical considerations

The study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board (IRB) of Hossana College of Health Sciences (Reference Number: IRB-2025–045).

All participants provided written informed consent prior to enrollment. The consent form explained the study purpose, procedures, voluntary nature of participation, and the right to withdraw at any time without consequences. No incentives were offered for participation.

Confidentiality was ensured by removing all identifying information from data files. Questionnaires and interview transcripts were identified only by participant codes. All data were stored on a password-protected computer accessible only to the principal investigator.

Results

Descriptive Statistics

Participant Characteristics: Of the 213 participants, 132 (62.0%) were female, and 81 (38.0%) were male. The mean age was 32.4 years (SD = 7.2, range: 22–58). Regarding professional roles, 173 (81.2%) were clinical staff (nurses, midwives, health officers, medical laboratory technicians, pharmacists) and 40 (18.8%) were non-clinical staff (administrators, cleaners, guards, data clerks). Years of experience ranged from 0.5 to 28 years (M = 6.8, SD = 5.1).

EI, CM, and WPE Scores: Table 1 presents descriptive statistics for the main study variables.

Table 1.

Descriptive Statistics for EI, CM, and WPE (N = 213)

Variable	Mean	Std. Deviation	Cronbach's Alpha	Possible Range	Actual Range
EI (Emotional Intelligence)	40.17	6.237	0.87	10–50	24–50
CM (Conflict Management)	40.23	6.609	0.84	10–50	23–49
WPE (Workplace Performance Effectiveness)	22.30	4.10	0.88	7–35	19–35

Source: Survey data collected by the researcher, 2024

The mean scores indicate relatively high levels of both EI and CM among participants. The mean WPE score of 22.30 (SD = 4.10) out of a possible 35 suggests moderate perceived workplace performance effectiveness.

Correlation analysis

A Pearson correlation analysis was conducted to examine the relationship between EI and CM. Results are presented in Table 2.

Table 2.

Correlation Analysis of CM and EI (N = 213)

Variable	CM	EI
CM (Conflict Management)	1.000	0.791**
EI (Emotional Intelligence)	0.791**	1.000

Note: **p < 0.01 (1-tailed)

A strong positive correlation was found between CM and EI (r = 0.791, p < 0.01). This indicates that healthcare workers with higher emotional intelligence scores also reported higher conflict management abilities. This relationship suggests that emotionally intelligent individuals are better equipped to handle workplace disagreements constructively.

Collinearity Diagnostics: To assess whether the high correlation (r = 0.791) posed a multicollinearity threat to regression analysis, the Variance Inflation Factor (VIF) and tolerance were calculated. The VIF for both EI and CM was 2.68, well below the conventional threshold of 5. Tolerance was 0.373, above the threshold of 0.2. These results indicate that multicollinearity was not a significant problem for the regression model.

Regression analysis

Multiple linear regression analysis was conducted to determine whether EI and CM significantly predicted Workplace Performance Effectiveness (WPE). Table 3 presents the model summary.

Table 3.

Model Summary—EI and CM Predicting WPE (N = 213)

Model	R	R Square	Adjusted R-Square	Std. Error of the Estimate
1	0.765	0.585	0.581	4.25*

Note: Predictors: (Constant), CM, EI Std. Error of the Estimate is approximate based on the corrected scale; verify with actual data

The model yielded R = 0.765 and R2 = 0.585, indicating that EI and CM together explained 58.5% of the variance in Workplace Performance Effectiveness. The adjusted R2 (0.581) confirmed the model's reliability, adjusting for the number of predictors. The ANOVA results, shown in Table 4, confirmed that the regression model was statistically significant.

Table 4.

ANOVA Results for Regression Model

Model	Sum of Squares	df	Mean Square	F	Sig
Regression	14,245.987	2	7122.993	159.087	< 0.001
Residual	10,118.939	210	48.185
Total	24,364.926	212

Note: Dependent Variable: WPE; Predictors: (Constant), CM, EI

The ANOVA results (F (2, 210) = 159.087, p < 0.001) confirmed that the regression model was statistically significant. This indicates that the combination of EI and CM reliably predicted workplace performance effectiveness. Table 5 presents the regression coefficients, showing the individual contribution of each predictor.

Table 5.

Regression Coefficients

Model	Unstandardized Coefficients	Standardized Coefficients	T	Sig	95% CI for B
	B	Std. Error	Beta			Lower	Upper
(Constant)	0.936	1.283		0.730	0.466	−1.592	3.464
EI	0.196	0.046	0.303	4.255	< 0.001	0.105	0.287
CM	0.280	0.044	0.455	6.397	< 0.001	0.194	0.366

Note: Dependent Variable: WPE (Workplace Performance Effectiveness)

Interpretation of Coefficients:

• Emotional Intelligence (EI): For each one-unit increase in EI score, WPE increased by 0.196 units (B = 0.196, β = 0.303, t = 4.255, p < 0.001). This indicates that EI makes a significant, moderate contribution to workplace performance, even after accounting for conflict management.

• Conflict Management (CM): For each one-unit increase in CM score, WPE increased by 0.280 units (B = 0.280, β = 0.455, t = 6.397, p < 0.001). The standardized coefficient (Beta = 0.455) is larger than that for EI, indicating that conflict management had a stronger predictive influence on workplace performance effectiveness in this model.

The regression equation can be written as: WPE = 0.936 + 0.196(EI) + 0.280(CM).

Qualitative results

To complement and contextualize the quantitative findings, semi-structured interviews were conducted with 12 healthcare managers (4 from each of the three health centers: Hossana, Lichamba, and Bobicho). Participants included department heads, nurse managers, and facility administrators. Interviews lasted between 25 and 45 min (average duration: 32 min), were audio-recorded, transcribed verbatim, and analyzed using thematic analysis following the six-phase framework of [18]. Two independent coders achieved strong inter-rater reliability (Cohen's κ = 0.84). Four major themes emerged from the analysis, each explicitly linked to the quantitative results.

Theme 1: Emotional awareness reduces daily conflicts

Managers reported that recognizing and controlling their own frustrations made it possible to calm employee tensions before the impending conflict would usually occur. This strengthens the finding of a strong positive correlation between EI and CM (r = 0.791, p < 0.01).

One of the managers at Hossana Health Center explained,

“When I notice I am becoming frustrated, I step back before responding. This simple act has prevented many arguments between nurses on my ward. If I react immediately with anger, the situation only gets worse. If I pause and then speak more calmly, staff are more likely to cooperate.” (Manager 3, Hossana Health Center).

Another manager at Lichamba Health Center said,

“Employees come to me with complaints almost every single day. If I respond emotionally, like shouting, and take a side, the conflict gets worse. If I listen first and calm my tone and acknowledge how they feel rightfully, we can come to a solution in minutes.” (Manager 7, Lichamba Health Center).

A third manager said,

“Managing staff here is stressful, but I have realized that my mood is like a beam of light to every staff member in that department. I have to stay calm for my team. If I lose my temper, they all become angry. Being aware of how I feel here is a must.” (Manager 10, Bobicho Health Center).

Those accounts show that managers with emotional intelligence can better resolve employee conflicts and are in line with the finding that EI can significantly affect job performance. (β = 0.303, p < 0.001).

Theme 2: Conflict management training is largely absent

Despite recognizing the importance of conflict resolution skills, most managers reported receiving no formal training in conflict management. This theme highlights a critical gap between the high self-reported CM scores (M = 40.23, SD = 6.609) and the absence of institutional support for developing these skills.

One manager stated candidly,

"I have been a manager for five years. I have never attended a single workshop, seminar, or course on handling workplace conflicts. Everything I know comes from trial and error, mostly error, to be honest. I learn from my mistakes." (Manager 9, Bobicho Health Center).

Another manager expressed frustration:

"We deal with conflicts every single day between doctors and nurses, between shifts, over scarce resources like gloves and beds. But there is no guidance from the district health office. No training. No protocols. We are completely on our own." (Manager 2, Hossana Health Center).

A third manager noted:

"When I was promoted to this position, I received training on budgeting, reporting, and supervision. But nothing on conflict management. Yet conflict is what takes up most of my time. It does not make sense." (Manager 11, Bobicho Health Center).

This theme contextualizes the quantitative finding that CM was the stronger predictor of WPE (β = 0.455, p < 0.001). Despite high self-reported CM scores, the lack of formal training suggests that managers rely on innate or informally acquired skills rather than evidence-based strategies.

Theme 3: Workload and resource scarcity fuel interpersonal tensions

Managers found high patient loads, persistent staff shortages, and limited medical supplies as underlying sources of staff conflicts. This topic provides background for assessing why even emotionally knowledgeable personnel may encounter conflicts under resource-constrained conditions, and it correlates with the Job Demands-Resources (JD-R) model underpinning this study.

One manager described the daily reality:

"When there are not enough gloves, not enough beds, not enough medicine, nurses blame each other. ‘You took the last box.' 'You did not order on time.' The real problem is the system the shortage is not anyone's fault but the anger comes out between colleagues because they cannot yell at the ministry." (Manager 5, Lichamba Health Center).

Another manager explained the morning shift dynamic:

"Morning shifts are the worst. Everyone is tired from working double shifts. There are too many patients waiting. Supplies are missing from the night before. Arguments start within the first hour over who used the last syringe, who did not restock, whose turn it is to handle a difficult patient." (Manager 11, Bobicho Health Center).

A third manager linked resource scarcity directly to staff turnover:

"Last year, I lost three good nurses. Not because of salary but because they could not handle the daily fighting over resources. The conflict wore them down. They said, 'I did not come to healthcare to argue about gloves.' That broke my heart." (Manager 4, Hossana Health Center).

This theme shows that EI and CM training alone may be ineffective if systemic issues (workload, resources) remain unresolved. The JD-R paradigm proposes that job demands (high workload) and job resources (supply and staffing) interact; when demands exceed resources, even talented individuals struggle to maintain performance.

Theme 4: Managers use informal, relationship-based strategies

In the absence of official conflict resolution rules or training, managers depended on personal ties, informal mediation, and culturally grounded tactics to resolve disputes. This theme explains how managers achieved relatively high self-reported CM scores without formal training.

One manager described a structured, informal approach:

"When two staff members are fighting, I take them aside separately first. I let each person explain their side without interruption. Then I bring them together. I ask each to say what they need from the other. Most of the time, they realize it was a misunderstanding, a missed handover, a forgotten task. They apologize, and we move on." (Manager 1, Hossana Health Center).

Another manager used a culturally familiar strategy:

"Tea breaks are my secret weapon. When people are fighting, I invite them to sit with me and drink tea. In Ethiopian culture, sharing tea is a sign of peace. In a relaxed setting, away from the ward, they talk more openly. By the time the tea is finished, the conflict is usually resolved." (Manager 6, Lichamba Health Center).

A third manager emphasized relationship-building:

"I make an effort to know my staff personally, their families, their challenges, and their hopes. When conflict happens, they trust me to be fair because they know I care about them. Without that trust, no mediation would work." (Manager 12, Bobicho Health Center).

One manager acknowledged the limitations of informal strategies:

"These informal methods work most of the time, but they are not sustainable. They depend entirely on my personality and my relationships. If I leave, there is no system left behind. We need formal training and written procedures." (Manager 8, Lichamba Health Center).

This theme suggests that while CM scores were high, the strategies used are informal, person-dependent, and may not be sustainable without institutional support.

Summary of qualitative findings

The results of the qualitative interviews showed that although managers are aware of the importance of emotional intelligence in lowering day-to-day conflicts, they are not formally trained in conflict resolution. Interpersonal conflicts were found to be mostly caused by a lack of resources and a heavy workload, which forced managers to turn to unofficial, relationship-based tactics such as separate mediation sessions and culturally rooted customs like coffee sharing. These findings support and contextualize the quantitative results, which showed a strong positive correlation between EI and CM (r = 0.791, p < 0.01) and a combined contribution of EI and CM to workplace performance effectiveness (R² = 0.585). The qualitative evidence suggests that the high self-reported CM scores may reflect innate or informally acquired skills rather than the result of structured institutional training.

Discussion

Using both qualitative and quantitative methodologies, this study investigated the relationship between emotional intelligence (EI), conflict management (CM), and workplace performance effectiveness (WPE) among healthcare professionals in Hossana Town, Central Ethiopia. The findings highlight the importance of these non-technical skills in resource-constrained healthcare settings and point out significant flaws in the institutions' support and training programs.

Levels of emotional intelligence and conflict management

Both EI and CM were comparatively high among the study's healthcare participants. The average CM score was 40.23 with a standard deviation of 6.609, while the average EI score was 40.17 with a standard deviation of 6.237. These results support Rahim's [40] argument that conflict resolution is a talent that can be gained in team-based environments and Goleman's [28] assertion that emotional intelligence is a common and crucial skill for good job performance.

These results are consistent with those of [46] who discovered that EI scores among nurses in public hospitals varied from 38.5 to 42.1. The scores here, however, are somewhat higher than those found in Bahir Dar, Ethiopia, where [25] found a connection between poor emotional regulation and high levels of work stress. This discrepancy may result from variations in work situations, resource accessibility, or institutional support levels among Ethiopia's various regions. These conclusions were deepened by insights from the qualitative interviews, which showed that managers frequently used informal, relationship-driven conflict resolution techniques. Even in the absence of formal instruction, this could account for the comparatively high self-reported CM scores.

Relationship between emotional intelligence and conflict management

The high positive connection between EI and CM (r = 0.791, p < 0.01) underscores their interdependence. This finding is consistent with past research linking emotional regulation to constructive conflict resolution [30, 48]. Healthcare personnel who acknowledge and regulate their emotions may be better equipped to understand colleagues' viewpoints and develop mutually acceptable solutions during conflicts.

The amplitude of this association (0.791) exceeds some other findings (e.g., O'Boyle et al., [37], found r = 0.45–0.65). Several theories may account for this stronger link. First, the high-stress healthcare context may regularly activate emotional abilities in conflict situations, reinforcing their link. Second, shared method variance (both components measured via self-report) may have overstated the correlation. Third, the particular cultural context of Ethiopian healthcare, where hierarchical relationships and collectivist ideals are prominent, may require the simultaneous application of EI and CM abilities. In such settings, healthcare personnel often need to manage emotions effectively while maintaining harmonious interpersonal relationships and resolving workplace disagreements. This context may strengthen the connection between EI and CM, thereby contributing to the stronger association observed in the present study. Importantly, multicollinearity diagnostics (VIF = 2.68; tolerance = 0.373) indicated that this connection did not invalidate the regression model.

The qualitative findings supported this statistical link. Managers regularly indicated how emotional awareness helped them de-escalate disputes before they escalated. As one boss observed, "If I react emotionally, the issue worsens. But if I listen first and regulate my tone, we identify a solution quickly." The narrative evidence supports the quantitative finding that EI and CM are closely linked in daily practice.

Predictive power of EI and CM on workplace performance

The combination of EI and CM accounted for 58.5 percent of the variance in workplace performance effectiveness (R2 = 0.585, F(2,210) = 159.087, p < 0.001). "The sizeable amount of variation accounted for by these two non-technical factors indicates that investments in enhancing their levels can lead to measurable improvements in the healthcare services delivered by staff."

The effect of conflict management was larger (β = 0.455, p < 0.001), and thus more influential in predicting workplace performance effectiveness than emotional intelligence (β = 0.303, p < 0.001). Thus, these data provide empirical support for Carmeli’s (2003) conceptualization of EI as an underlying factor enabling individuals to engage in behaviors effectively. De Dreu (2008) has argued that CM directly addresses how individuals make decisions and collaborate, which is likely why it was more powerful in explaining workplace performance effectiveness than EI.

In practical terms, this study provides evidence that providing healthcare workers with instruction in concrete conflict resolution strategies (e.g., negotiation, mediation, interest-based problem-solving) will be a more direct way to improve workplace performance than providing them with instruction in EI alone.

These results are consistent with a large body of research indicating that when EI is combined with appropriate leadership and work design practices, it produces significant increases in both employee performance and innovation [4, 5, 7]. Moreover, the fact that CM produced a larger β than EI suggests that providing employees with skills they can apply to resolve conflicts in the workplace will be more directly related to improving workplace effectiveness than developing EI.

Moreover, the qualitative data obtained from managers indicated a critical caveat. Managers reported very high self-rated scores on CM, but all managers reported that they had never received formal training in CM. For example, one manager said, "I've been a manager for five years. I've never gone through a single workshop about dealing with workplace conflicts. Everything I know has come from trial and error. “Thus, the high scores on CM appear to represent either an individual difference (i.e., an innate ability) or an untested strategy developed informally rather than based upon formal education/training. Moreover, if formal CM training were provided to increase the level of CM, we hypothesize that there would be greater improvement in workplace performance effectiveness.

The role of workload and resource scarcity

The qualitative interviews identified high patient loads, staff shortages, and inadequate supplies as underlying drivers of interpersonal conflicts. This finding is consistent with the Job Demands-Resources (JD-R) model [11, 12], which underpins this study's conceptual framework. According to the JD-R model, workplace outcomes are determined by the balance between job demands (e.g., workload, emotional demands) and job resources (e.g., autonomy, social support, supplies). When demands chronically exceed resources, burnout and reduced performance occur.

In this study, managers explicitly linked resource scarcity to staff conflicts. One manager explained: "When there are not enough gloves or beds, nurses blame each other. The real problem is the system, but the anger comes out between colleagues." Another noted, "Morning shifts are the worst. Everyone is tired, there are too many patients, and supplies are missing. Arguments start within the first hour."

These findings suggest that EI and CM training alone may be insufficient if systemic issues (workload, resource allocation) remain unaddressed. The JD-R model implies that interventions should target both individual skills (EI, CM) and organizational resources (staffing, supplies, and supportive policies) to achieve sustainable improvements in workplace performance.

Comparison with Ethiopian and international studies

The current findings align with previous Ethiopian research. [32] reported that healthcare facilities in Ethiopia where EI and CM training were implemented showed lower turnover intentions and higher patient satisfaction scores. Similarly, [49] found that job satisfaction among Ethiopian health workers was strongly predicted by interpersonal relationship quality and conflict resolution effectiveness.

However, the current study extends these findings by quantifying the combined predictive power of EI and CM (R2 = 0.585) and by demonstrating that CM is a stronger predictor than EI in this context. This has important implications for resource allocation in Ethiopian healthcare training programs: prioritizing CM training may yield more immediate improvements in workplace dynamics than general EI training alone.

Internationally, these findings are consistent with studies showing that transformational and inclusive leadership styles amplify the effects of EI and CM on employee outcomes [6, 9]b). Leaders who create psychologically safe environments and model emotional competence may help sustain the benefits of EI and CM training over time.

Recommendations for practice

Based on the integrated quantitative and qualitative findings, the following recommendations are offered:

• 1. Prioritize Conflict Management Training. Given that CM was a stronger predictor (β = 0.455) than EI (β = 0.303), health centers should initially invest in structured CM training programs. Modules should include negotiation, mediation, interest-based problem-solving, and de-escalation techniques.

• 2. Integrate EI Enhancement as Foundational Support. EI training should complement CM training, focusing on self-awareness, emotion regulation, empathy, and active listening. The strong correlation between EI and CM (r = 0.791) suggests these skills develop together and reinforce each other.

• 3. Implement Formal Conflict Resolution Protocols. In the absence of formal procedures, managers currently rely on informal, relationship-based strategies that are person-dependent and unsustainable. Health center administrators should establish written conflict resolution policies with clear pathways for addressing disputes.

• 4. Address Systemic Resource Constraints. The qualitative findings indicate that workload and resource scarcity are underlying drivers of interpersonal conflict. EI and CM training will be more effective when accompanied by organizational efforts to improve staffing levels, supply chains, and workload distribution.

• 5. Provide Supervisory Training for Managers. Nurse managers and department heads should receive advanced training in coaching staff on EI and CM skills. Leadership styles that foster psychological empowerment and inclusion have been shown to amplify the effects of EI and CM on employee outcomes [6, 9].

• 6. Incorporate EI and CM into Performance Evaluations. Healthcare institutions should recognize emotional intelligence and conflict management alongside technical skills in performance reviews and promotion criteria.

Policy implications

This study's results suggest multiple policies for multiple health service levels. Findings suggest that the Ministry of Health should include conflict management (CM) as a mandatory subject for ongoing training of health care managers in public health centers. The results are justified since CM training was not offered to any of the managers in this study, and CM was a better predictor of work performance than emotional intelligence (EI) (CM β = 0.455 versus EI β = 0.303). Results from this study suggest that, at the regional level, health bureaus are expected to allocate dedicated budgets for training EI and CM in primary health centers, especially in resource-poor settings. At the institutional level, health center managers should include EI in the workplace development and staff promotion frameworks. The health center’s development frameworks should embrace collaboration. In addition, the framework should include conflict management. In this regard, HR departments should develop and establish conflict management and resolution policies. These policies will provide staff the means to resolve conflicts and create a method for staff to bring forth workplace issues before they become bigger problems. Lastly, CM and EI training should be integrated into the curricula of all health training institutions. The aim of this training should be to ensure an adequate and modern health workforce.

Limitations

Several limitations should be acknowledged:

• 1. Cross-sectional design. Data were collected at a single time point, which prevents the establishment of causal relationships between EI, CM, and WPE. Longitudinal studies are needed to determine directionality.

• 2. Self-report measures. All quantitative data were collected via self-report questionnaires, which may be subject to social desirability bias and common method variance. Future studies should incorporate supervisor ratings, peer assessments, or objective performance data (e.g., patient outcomes, error rates).

• 3. Single geographic location. The study was conducted only in Hossana Town, which may limit generalizability to other Ethiopian regions or countries. Replication in diverse settings (urban vs. rural, different regional states) is recommended.

• 4. High EI-CM correlation. While multicollinearity tests indicated no statistical violation (VIF = 2.68), the strong relationship between predictors (r = 0.791) suggests that future research should explore whether EI and CM represent distinct constructs or different facets of a broader interpersonal competence.

• 5. Limited qualitative component. Although this study included qualitative interviews with 12 healthcare managers to contextualize the quantitative findings, the qualitative sample was small and restricted to managerial perspectives only. Frontline staff were not interviewed, and the findings may not capture the full range of lived experiences. Future mixed-methods research should include both managers and frontline workers with a larger qualitative sample.

• 6. Emerging technologies not examined. This study did not examine the potential role of AI-driven human resource management practices in supporting EI and CM development, an area identified as promising for future research [9].

Conclusions

This study identifies emotional intelligence and conflict management as critical competencies for healthcare practitioners working in Ethiopian health centers. This study suggests that effective workplace performance is significantly associated with both emotional intelligence and conflict management and explains 58.5% of the total variance. Among the two competencies, conflict management was the strongest predictor of workplace performance. Therefore, training staff to manage conflict is likely to improve the work environment more rapidly than training in emotional intelligence.

The strengths of EI and CM are positively correlated at 0.791, p < 0.01, suggesting they often coincide at the same level in the same population in the same context. Health workers who are able to identify feelings and manage them are likely able to manage conflicts in the health workplace more constructively.

But, according to the qualitative data, the managers demonstrated a gap in awareness. There was a significant inconsistency in their data, where self-reported CM scores were high, yet all of them lacked any formal training in CM. Managers focused on informal relationship strategies and personal, and likely temporary, interventions like separate tea and mediation sessions. In addition, the managers cited numerous stresses on their time and resources as direct causes of the workplace conflicts, leading to the conclusion that training in EI and CM may be of limited use under these additional constraints.

It is suggested that EI and CM training be incorporated into staff training programs and that formal, trust-based conflict interventions be established, along with recognition and reward systems for these skills and the removal of the resource constraints on the system. If these are done together, it is likely that positive outcomes will be achieved, such as increased employee satisfaction and decreased employee turnover, improved employee engagement, and enhanced health service delivery.

To develop these ideas further, longitudinal studies are recommended that use supervisor-rated metrics of performance rather than self-reports, as well as consideration of the constraining impacts of various cultures and styles of leadership on the workplace, and the use of an innovative approach incorporating AI in the HRM space in support of EI and CM [9] in the design of the studies. There should be a greater focus on frontline workers as the interview subjects in qualitative research on workplace conflict in the health service.

Authors’ contributions

Author: Ashenafi Woldemichael Woime (PhD) Competing Interests: The author declares no competing interests.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

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

Declarations

Ethical approval and consent to participate

This study was approved by the Institutional Review Board (IRB) of Hossana College of Health Sciences (Reference No. IRB-2025–045). All procedures were performed in accordance with the approved protocol.

Consent for publication

Not applicable. This manuscript contains no person's data in any form (including details, images, or videos) that would compromise anonymity.

Competing interests

The authors declare no competing interests.