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. 2025 Oct 8;35(4):1620–1632. doi: 10.1111/jocn.70128

Development and Validation of a Negative Emotions Scale for Public Health Nurses Engaged in Child Abuse Prevention Activities

Haruka Yokobori 1,✉, Chikako Honda 1,2, Hiroshige Matsumoto 1,2, Akari Maeda‐Suzuki 1,2, Kyoko Yoshioka‐Maeda 1,2
PMCID: PMC12964507  PMID: 41059770

ABSTRACT

Aims

To assess the reliability and validity of a negative emotion scale for public health nurses conducting child abuse prevention activities.

Design

A four‐phase mixed method design.

Methods

Participants were public health nurses with experience in child abuse prevention across Japan. The initial scale was developed and refined based on previous studies, expert panel reviews, interviews with public health nurses, and a questionnaire‐based pilot study. In 2024, 549 public health nurses completed a questionnaire on scale items. Item analysis, exploratory factor analysis, confirmatory factor analysis, comparisons with a preexisting scale, the number of times negative attitudes and the types of behaviours exhibited by parents were used to narrow the scale and assess its psychometric properties.

Results

Item analysis and exploratory factor analysis reduced the scale to 15 items on two factors: ‘negative emotions toward aggressive and emotional attitudes’ and ‘negative emotions toward rejecting and uncooperative attitudes.’ Confirmatory factor analysis indicated a good model fit. The Cronbach's alpha was high, and the negative emotions scale score positively correlated with the pre‐existing scale, negative attitudes and parental behaviours.

Conclusions

The Cronbach's alpha coefficient and other factors confirmed the scale's reliability, and correlations with other scales confirmed its validity.

Implications for the Profession

Evaluating negative emotions provides critical insights into the quality of support and its influence on psychological well‐being.

Impact

By assessing negative emotions that public health nurses find difficult using this scale, the support system for them can be examined.

Reporting Methods

STROBE checklist for cross‐sectional studies was followed.

Patient or Public Contribution

Public health nurses were involved in the generation of items for the scale. Their perspective was sought in determining the items for the scale.

Trial and Protocol Registration

Registered in the UMIIN Clinical Trial Registry (UMIN‐CTR ID UMIN000054650).

Keywords: emotional labour, negative emotions, public health nursing

Summary.

  • What does this paper contribute to the wider global clinical community?
    • ○
      Assessing the negative emotions of public health nursing professionals working in the community and contributing to recommendations for the need for a support system in the workplace.
    • ○
      It is a basic resource for research on the evaluation of the effects of negative emotions.

1. Introduction

Child abuse is a serious global human rights issue owing to its adverse effects on children's health, life, development and dignity. The World Health Organization reports that approximately 300 million, or three‐quarters of the world's 400 million children aged 2–4 years, experience physical or psychological abuse by their parents or caregivers (World Health Organization 2020). Nurses conduct home visits and significantly prevent child abuse more effectively than non‐professionals (Olds et al. 2019). Moreover, worldwide, public health nurses (PHNs), frontline workers and coordinators have identified and supported parents and children in cases of child abuse (Jack et al. 2021). PHNs are defined as nurses who provide child abuse prevention as a public health nursing activity to community residents. Although the name of PHNs may differ in different countries, such as health visitors in the United Kingdom (Hemingway et al. 2013), PHNs often experience negative emotions toward parents owing to their negative attitudes. However, studies on negative emotions among PHNs are scarce. Negative emotional responses experienced by PHNs in child abuse prevention can hinder effective support, necessitating the development of a new scale tailored to their unique work context.

2. Background

In Japan, 214,843 victims of child abuse were reported in 2022 (Statistics Bureau 2025). PHNs employed by local governments play a crucial role in preventing child abuse as they can access and assess almost all parents with infants while providing municipal services, such as home visits and health checkups (Yokobori et al. 2022; Yoshioka‐Maeda and Fujii 2022).

PHNs often encounter parents' negative attitudes toward child abuse prevention (Honda et al. 2023; Taylor et al. 2017). Negative attitudes are defined as clients' negative emotional expressions toward support providers, such as yelling and insults (Grandey et al. 2013). These behaviours have been described in various terms, such as ‘mistreatment by patients (Goussinsky and Livne 2016),’ ‘workplace violence (Rossi et al. 2023),’ ‘difficult patient (Bailey et al. 2023),’ ‘patient aggression (Wu et al. 2025),’ ‘incivility from patients (Campana and Hammoud 2015).’ Healthcare workers, including nurses, are more likely than non‐healthcare workers to experience such negative attitudes owing to the emotional, intimate nature of their work (LanctÔt and Guay 2014). In fact, three‐fourths of hospital employees experienced negative attitudes toward clients within a year (Eker et al. 2012).

Negative attitudes from the clients can lead to emotional distress and reduce the quality and frequency of services. Service providers naturally have ‘negative emotions’ toward clients when they experience negative attitudes from clients. However, the provider suppresses these emotions and engages clients positively to provide smooth support (Wang et al. 2011). This process is called emotional labour (Grandey 2000; Hochschild 1983). Previous studies in hospital settings have shown that negative emotions lead to depersonalization and burnout (Goussinsky and Livne 2016; Szczygiel and Mikolajczak 2018; Viotti et al. 2015), decreased frequency of support (Goussinsky 2020), decreased motivation to support, leave of absence and turnover among nurses (ten Hoeve et al. 2020). Studies conducted in hospital settings have shown that negative emotions contribute to depersonalization, burnout, decreased motivation to support and increased turnover among nurses, especially those with limited work experience (Kuruppu et al. 2022; Leonard et al. 2020).

A survey using a scale is needed to determine the impact of negative emotions on PHNs. Despite the seriousness of negative emotions' consequences, there are key challenges in measuring negative emotions among PHNs. First, existing scales are often developed for hospital‐based nurses and are not suitable for use in community settings where the nature of support and client relationships differs significantly (Szczygiel and Mikolajczak 2018). Secondly, items must be designed for ease of response. Several studies have measured negative emotions using the Positive and Negative Affect Schedule (PANAS) (Bedyńska and Żołnierczyk‐Zreda 2015; Wang et al. 2011; Watson et al. 1988). Although PANAS is a scale that answers only personal feelings, it has the challenge of making it difficult to recall specific situations. Third, there is a conceptual gap in how negative emotions are understood in public health nursing. The measurements by PANAS include emotionally descriptive terms like ‘distressed’ and ‘scared,’ which may not adequately capture the nuanced emotional labour involved in PHNs' community‐based roles and may be challenging to respond to accurately (Acquadro Maran et al. 2018; Chi et al. 2018; Diefendorff et al. 2008; Georgia and Richard 1998; Lin 2020). In previous studies, holding negative emotions is seen as undesirable, which may lead to self‐blame among professionals. However, from the perspective of emotional labour theory, negative emotions are a natural response to negative client attitudes and should be acknowledged rather than denied. It may be easier to visualise the burden on the PHNs if negative emotions can be self‐reported.

Therefore, developing a new self‐report scale that captures PHNs' negative emotions in the context of child abuse prevention while considering the emotional labour they perform is essential. A new scale would not only allow PHNs to reflect on their emotional burden but also inform organisational support and training programs aimed at sustaining effective service delivery.

3. The Study

3.1. Aims

This study aimed to generate and evaluate the reliability and validity of a negative emotions scale for PHNs conducting child abuse prevention activities. The study was guided by the Best Practices for Developing and Validating Scales for Health, Social and Behavioural Research (Boateng et al. 2018), a standard for scale development.

3.2. Design

This study was conducted in four phases. Phase 1 was domain identification and draft item generation for the scale. Phase 2 was item selection of the scale through interviews with PHNs. Phase 3 was an evaluation of content validity through the questionnaire‐based pilot test. Phase 4 was a cross‐sectional survey to confirm construct and convergent validity, discriminant internal validity and reliability. All data correction was conducted in Japan. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Appendix S1) (von Elm et al. 2015).

3.3. Phase 1: Item Generation

Domain identification and draft item generation were conducted in Phase 1 between September and December 2023. First, two conceptual frameworks of the scale were established concerning previous studies describing emotional labour in PHNs (Honda et al. 2023).

3.3.1. Negative Emotions Toward Aggressive and Emotional Attitudes

As negative emotions experienced by PHNs support, Honda identifies ‘negative emotions toward residents with aggressive attitudes’ and ‘negative emotions toward residents with emotional complaints.’ These two negative emotions are summarised in this framework because clients have an invasive attitude in common.

3.3.2. Negative Emotions Toward Rejecting and Uncooperative Attitudes

As negative emotions experienced by PHNs' support, Honda identifies ‘negative emotions toward residents without behaviour change’ and ‘negative emotions toward residents concealing their true feelings.’ These two negative emotions are summarized in this framework because they share the fact that clients avoid PHNs' support.

Second, we developed draft items with reference to studies that identified negative emotions among PHNs and nurses (Dmytryshyn et al. 2015; Honda et al. 2023; Kageyama and Yokoyama 2018; Leonard et al. 2020; Taylor et al. 2017).

The expression of emotions in the scale was based on the previous study that identified the types of negative emotions experienced by nurses and other healthcare professionals in their work (Martin et al. 2015; Szczygiel and Mikolajczak 2018) and nine types of negative emotions were extracted: ‘anxiety, fear, confusion, frustration, anger, irritation, sadness, disappointment and melancholy. All nine negative emotions are included in this scale. A thesaurus was referenced to ensure that the emotional expressions were more accurate. To make it easier to recall specific situations, situations that caused negative emotions were extracted using the same procedure, and draft items were created by combining situations and emotions. Next, the co‐researchers reviewed the draft items, and items that fit within the conceptual framework of PHNs' negative emotions were selected. In this process, duplicate items were discarded, and similar items were integrated. Consequently, 20 draft items were created. The response method was a 5‐point Likert scale, ranging from ‘1. never’ to ‘5. always’.

3.4. Phase 2: Item Selection of the Scale Through Interviews for PHNs

Interviews were conducted to examine the appropriateness of the conceptual framework and content of the proposed scale between December 2023 and January 2024. Six PHNs with experience in child abuse prevention were recruited using snowball sampling. The first participant was recruited through the authors' professional network. Subsequent participants were introduced to the study by the initial participant. To capture perspectives of individuals with different career levels, novice, mid‐level and expert PHNs were included. They also checked whether the combination of ‘experience of negative attitudes’ and ‘emotion’ in the draft items was comfortable. We also asked if there were any items that should be added or deleted.

3.5. Phase 3: Evaluation of Content Validity Through the Pilot Survey

3.5.1. Sampling and Data Collection

A pilot study was conducted to examine the content validity of the scale and to obtain suggestions for modifications between February and May 2024. A questionnaire survey of PHNs was conducted in March 2024, May 2024 and June 2024. Inclusion criteria were PHNs (a) who had been working in municipal maternal and child health departments for over 1 year, including those who moved to another department within 6 months, and (b) who had experience in case management for parents of children or pregnant women with a risk of abuse for over 1 year. PHNs who have mental disorders owing to the psychological burden of study participation were excluded. The required sample size was estimated according to Kline's (1994) recommendation of at least a sample size of 100 participants and 20 times the number of factors in factor analysis (Kline 1994). An additional participant was excluded from the analysis owing to a lack of experience with negative emotions. Convenience sampling was conducted. Research participation requests were sent to 11 municipalities; however, permission to recruit participants was obtained from only eight of those municipalities. Questionnaires were then distributed to eligible PHNs in these eight municipalities.

3.5.2. Measures, Instrument With Validity and Reliability/Data Source

Demographic data on the participating PHNs was collected, including age, sex and duration of work experience.

Participants were asked to recall whether they had experienced negative attitudes from parents and one eligible case that PHNs had more recently experienced. We also asked participants about the demographic characteristics of the case, including parents' age, gender, child's age, types of abuse, present illness and contents of PHNs' support. Participants filled out a scale that asked, ‘In the 6 months, how much of the following emotions did you experience when interacting with clients?.’

To assess convergent validity, the Japanese version of PANAS (Watson et al. 1988; Sato and Yasuda 2001) was used. This scale is a 6‐point Likert‐type scale that asks about an individual's negative or positive mood in the present period, ranging from 1 (not at all) to 6 (extremely). We consider this scale valid for use because negative moods measured by the PANAS correlate with negative emotions (Szczygiel and Mikolajczak 2018). In this study, Cronbach's alpha for Japanese PANAS was 0.86. To measure criterion‐related validity, we asked about PHNs' difficulty in providing support, the number of times negative attitudes were reported, and the types of behavior exhibited by parents.

3.6. Phase 4: Main Survey to Establish the Construct Validity and Reliability

3.6.1. Sampling and Data Collection

The main survey was conducted from June 2024 to September 2024. Inclusion and exclusion criteria are the same as in phase 3. There being 1741 municipalities in Japan, they were stratified into three categories: (a) large cities (special wards, designated cities and core cities), (b) medium‐sized cities other than (a) nor (c) and (c) towns and villages. Within each stratum, 40% of the municipalities were randomly selected using the RAND function in Excel (Microsoft, Redmond, WA, USA) before sending the request letters, excluding areas with huge earthquakes in 2024 (Figure 1). Informed consent letters were sent by post to the manager of the Maternal and Child Health Department in each municipality and sent back to participate in the survey and the number of PHNs in the municipality. Informed consent letters were sent to PHNs in the maternal and child health departments. Questionnaires were distributed to PHNs by the manager of each participating Maternal and Child Health Department. PHNs who were interested in participating in the study voluntarily completed the questionnaire and individually returned it to the researchers.

FIGURE 1.

FIGURE 1

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Flowchart in the main survey. (a) Large city (special wards, designated city, core city), (b) middle‐sized city (city excluded a), (c) town and village.

3.6.2. Measures, Instrument With Validity and Reliability/Data Source

The data in phase 3 were collected in the same way. In this study, Cronbach's alpha for the Japanese PANAS was 0.86.

3.7. Statistical Analysis

Item analysis was performed to investigate the internal consistency of the scale. The exclusion criteria for item analysis were confirmation of ceiling and floor effects (mean + SD > 5, mean—SD < 0), distribution (never and sometimes together accounting for > 75% of the sample), good–poor analysis (no significant difference between the highest and lowest scoring groups) and item‐total analysis (correlation coefficient < 0.30).

After item analysis, the items were examined using exploratory factor analysis with Promax rotation to investigate construct validity. The least squares method was used in the pilot survey, and the maximum likelihood method in the main survey. We sequentially determined the optimal number of factors using the Kaiser‐Guttman (eigenvalues > 1.0) and a scree plot. Item loadings must exceed 0.40. The reliability of the scale and each factor was evaluated using Cronbach's alpha > 0.70 and the Spearman‐Brown > 0.70 for the reliability coefficient. A confirmatory factor analysis was performed on the remaining items from the exploratory factor analysis. Goodness of fit (GFI), adjusted GFI (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA) were used to evaluate the model fit. The model was accepted if the GFI, AGFI and CFI were ≥ 0.90 and RMSEA ≤ 0.08 (Boateng et al. 2018). Furthermore, a correlational analysis was conducted to evaluate criterion‐related validity and convergent validity. The average variance extracted (AVE) was used as a criterion for convergent validity (AVE > 0.5) and discriminant validity (AVE > square of factor correlations) (Fornell and Larcker 1981). Data from the analysis were excluded if more than 20% of the scale items were missing or if all items on the scale had the same answer choice. In phase 3, the mean value was entered by dividing the total number of items without missing items for the same respondent by the number of items without missing items to handle missing data. In the main survey, multiple imputation (MI) methods were applied to handle missing data (Enders 2010). IBM SPSS version 29 and SPSS Amos version 29 were used for all the statistical analyses.

3.8. Ethical Considerations

This study was approved by the Ethics Committee of the University of Tokyo School of Medicine (protocol code: 2023281NI‐(2)) and was registered in the UMIIN Clinical Trial Registry (UMIN‐CTR ID UMIN000054650). Informed consent letters were sent to PHNs in the maternal and child health departments. Questionnaires were distributed to PHNs by the manager of each participating Maternal and Child Health Department. PHNs who were interested in participating in the study voluntarily completed the questionnaire and individually returned it to the researchers.

4. Results

4.1. Phase 1 and Phase 2

The first draft of the scale consisted of 26 items. In phase 2, all participants were female, with a mean age of 33.2 years (SD = 8.7) and a mean of 8.5 years (SD = 8.0) of experience as PHNs. Most study participants expressed a desire for the scale to include support for pregnant women because PHNs support pregnancy in preventing child abuse after childbirth. Therefore, we specified in the questionnaire that support for pregnant women be included as a child abuse prevention activity. Nine items were modified for content and expression. Ultimately, 22 items were selected for the analysis (Appendix S2).

4.2. Phase 3: Pilot Test

Seventy‐eight PHNs from 8 municipalities responded to the questionnaire (response rate: 16.8%). Sixty‐five respondents who experienced negative parental attitudes were included in the analysis. Among them, 61 were female, and four were male, with a mean of 12.9 years (SD = 9.3) of experience as a PHN.

Table 1 presents the results of the exploratory factor analysis. Each factor was consistent with the conceptual framework, with Factor 1 consisting of 11 items and Factor 2 consisting of 11 items. Factor loadings ranged from 0.33 – 0.91, with one item below the criterion. Cronbach α = 0.92, Spearman‐Brown reliability coefficient = 0.95. The scale showed significant correlations with the PANAS, the number of times parents had negative attitudes, and the number of negative attitudes adopted by parents. No significant correlation was observed with the degree of difficulty in providing support. In the pilot survey, PHNs may have struggled to respond to the scale because they were asked to recall experiences from the past 3 months. The main survey was modified to ask about the experience of the cases over 6 months. We decided not to delete items owing to the small sample size in phase 3.

TABLE 1.

Phase 3 (pilot survey): exploratory factor analysis.

Conceptual flamework Scale item Factor loading score α
1 2
I 2. I was depressed about clients who complained for long periods. 0.91 −0.13 0.94
I 9. I was depressed by clients who repeatedly complained. 0.84 0.04
I 3. I was scared of clients who made statements that threatened my safety. 0.81 −0.07
I 1. I was scared of clients who reprimanded me in a loud voice. 0.81 −0.11
I 6. I was frustrated with clients making difficult requests. 0.79 −0.01
I 11. I was depressed about clients seeking more help than they needed. 0.77 −0.06
I 4. I felt confused by the client's baseless blame. 0.76 0.12
I 5. I was confused by the client's unexpected complaint. 0.75 0.04
I 10. I was scared of the client who seemed aroused. 0.75 0.04
I 8. I was annoyed at clients who made inconsistent complaints. 0.58 0.26
I 7. I was confused by clients who complained of mental instability. 0.54 0.20
II 15. I was concerned about a client who did not respond to my contact. −0.41 0.33 0.89
II 22. I was frustrated by the client's lack of response to the conversations. −0.20 0.85
II 17. I was frustrated with clients who could not follow the rules for support. 0.03 0.76
II 12. I was discouraged by the lack of behaviour change in clients after continued support. −0.12 0.75
II 13. I was frustrated with clients who did not accept my advice. 0.06 0.73
II 16. I was frustrated with the client for being reneged on my support plans. 0.04 0.71
II 19. I was frustrated with clients who reacted negatively to the improvement of their issues. 0.19 0.70
II 14. I was confused by the clients who refused the support I suggested. 0.11 0.69
II 21. I was agitated by clients who did not speak during our conversations. −0.12 0.69
II 20. I was annoyed with the client for clouding the facts. 0.04 0.68
II 18. I was confused by the client's negative reaction to support. 0.03 0.52
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Note: Least‐squares method with promax rotation without assuming the number of factors. Factor 1: ‘negative emotions toward aggressive and emotional attitudes’. Factor 2: ‘negative emotions toward rejecting and uncooperative attitudes’. Cronbach α: 0.92, Spearman‐Brown reliability coefficient = 0.95. The bold values indicates that these items belong to that dimension.

4.3. Phase 4

Figure 1 shows a flowchart of the phase 4 main survey. A total of 189 municipalities (18 large cities, 71 middle‐sized cities, and 100 towns and villages) participated in the survey. In total, 549 questionnaires were returned (response rate: 48.5%). Of these, 14 were excluded owing to less experience in the maternal and child health department, and 16 were excluded owing to incomplete data. Furthermore, 134 PHNs had no negative attitudes toward parents at risk of abuse. According to the concept of emotional labour, negative emotions are experienced by PHNs when they encounter negative attitudes, which may affect their psychological burden; therefore, these participants were excluded. Moreover, an evaluation of the validity of the scale required information regarding concrete experiences involving negative attitudes. Finally, data from 385 questionnaires were analysed.

4.3.1. Characteristics of the Participants

Table 2 shows the participants' characteristics. The mean number of experiences as PHNs was 14.3 (SD = 10.2), and 376 (97.9%) were female (Table 2).

TABLE 2.

Characteristic of participants of phase 4 survey.

n % (range)
Mean SD
Gender (n = 384)
Female 376 97.9
Male 7 1.8
Age (n = 384)
20's 70 18.2
30's 118 30.7
40's 112 29.2
50's~ 84 21.9
Years of experience as PHN 15.1 10.3 (1–44)
Years of experience as maternal and child health section 9.7 7.9 (1–36.5)
Years of experience as nursing professional 16.8 9.9 (1.3–47)
Educational background as nursing professional
Vocational training school 111 28.8
Junior collage 46 11.9
University 222 57.7
Graduate school 6 1.6
Educational background as PHN (n = 380)
Vocational training school 125 32.6
Junior collage 4 1.0
University 247 64.3
Graduate school 8 2.1
Overtime work (h/m) 11.6 12.6 (0‐70)
Number of PHNs in the section 12.5 15.7 (1‐105)
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Note: Missing data were excluded from each analysis and percentages for each item were calculated after excluding missing values.

4.3.2. Demographic Data of Parents at Risk of Abuse

Based on the cases reported by the participants, the mean supporting period (i.e., the number of years each PHN had spent providing support to clients) was 1.3 years (SD = 1.3). The parents who most commonly had negative attitudes toward PHNs were mothers (n = 334, 86.8%) and fathers (n = 86, 22.3%). The negative attitudes that PHNs experienced from parents at risk of abuse included complaints about support (n = 204, 53.0%) and support rejection (n = 163, 42.3%).

4.3.3. Results for Item Analysis

Four items were deleted because the scores were highly skewed, as more than 75% of the respondents scored 1 or 2 points. These items included ‘I was scared of clients who made statements that threatened my safety,’ ‘I was depressed about clients seeking more help than they needed,’ ‘I was agitated by clients who did not speak during our conversations,’ and ‘I was frustrated by the client's lack of response to the conversations.’ Three items were deleted because they had adjusted item‐total correlation scores of < 0.30 or > 0.70, and these items were not related to the domain under study (Table 3). These items include ‘I was annoyed at clients who made inconsistent complaints,’ ‘I was depressed by clients who repeatedly complained,’ and ‘I was concerned about a client who did not respond to my contact.’

TABLE 3.

Item analysis (n = 385).

Adjusted item‐total correlation Cronbach's alpha if item deleted Good‐poor analysis Exclusion because of item‐total correlation Exclusion because more than 75% of responses were 1 or 2 point
1. I was scared of clients who reprimanded me in a loud voice. 0.52 0.92 < 0.001
2. I was depressed about clients who complained for long periods. 0.61 0.92 < 0.001
3. I was scared of clients who made statements that threatened my safety. 0.58 0.92 < 0.001 ×
4. I felt confused by the client's baseless blame. 0.64 0.92 < 0.001
5. I was confused by the client's unexpected complaint. 0.59 0.92 < 0.001
6. I was frustrated with clients making difficult requests. 0.68 0.91 < 0.001
7. I was confused by clients who complained of mental instability. 0.58 0.92 < 0.001
8. I was annoyed at clients who made inconsistent complaints. 0.73 0.91 < 0.001 ×
9. I was depressed by clients who repeatedly complained. 0.70 0.91 < 0.001 ×
10. I was scared of the client who seemed aroused. 0.59 0.92 < 0.001
11. I was depressed about clients seeking more help than they needed. 0.55 0.92 < 0.001 ×
12. I was discouraged by the lack of behaviour change in clients after continued support. 0.44 0.92 < 0.001
13. I was frustrated with clients who did not accept my advice. 0.54 0.92 < 0.001
14. I was confused by the clients who refused the support I suggested. 0.49 0.92 < 0.001
15. I was concerned about a client who did not respond to my contact. 0.22 0.92 < 0.001 ×
16. I was frustrated with the client for being reneged on my support plans. 0.57 0.92 < 0.001
17. I was frustrated with clients who could not follow the rules for support. 0.63 0.92 < 0.001
18. I was confused by the client's negative reaction to support. 0.49 0.92 < 0.001
19. I was frustrated with clients who reacted negatively to the improvement of their issues. 0.59 0.92 < 0.001
20. I was annoyed with the client for clouding the facts. 0.61 0.92 < 0.001
21. I was agitated by clients who did not speak during our conversations. 0.55 0.92 < 0.001 ×
22. I was frustrated by the client's lack of response to the conversations. 0.52 0.92 < 0.001 ×
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Note: Cronbach α = 0.92.

4.3.4. Results of Factor Analysis for Construct Validity

Exploratory factor analysis was performed after item analysis. The number of factors was determined to be two based on one or more eigenvalues after the scree plot and interpretation (Figure 2). This analysis generated two factors that accounted for 54.4% of the total variance. An exploratory factor analysis with maximum likelihood using promax rotation was performed (Table 4). Given that no item had a factor loading less than 0.4 on the affiliation factor, 15 items with two factors were finally explained. The factor structure was defined as Factor 2: ‘negative emotions toward aggressive and emotional attitudes’ (8 items) and Factor 1: ‘negative emotions toward rejecting and uncooperative attitudes’ (7 items), consistent with the conceptual framework. These two factors were entered as latent factors in a confirmatory factor analysis model. All fit indices indicated good data‐model fit (Figure 3: GFI = 0.924, AGFI = 0.890, CFI = 0.952, RMSEA = 0.07).

FIGURE 2.

FIGURE 2

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Sclee plot confirming the retention of five factors. [Colour figure can be viewed at wileyonlinelibrary.com]

TABLE 4.

Exploratory factor analysis (n = 385).

Conceptual flamework Scale items Factor loading score α AVE
I II
II 13. I was frustrated with clients who did not accept my advice. 0.85 −0.11 0.90 0.51
II 12. I was discouraged by the lack of behaviour change in clients after continued support. 0.79 −0.17
II 19. I was frustrated with clients who reacted negatively to the improvement of their issues. 0.73 0.05
II 17. I was frustrated with clients who could not follow the rules for support. 0.69 0.11
II 20. I was annoyed with the client for clouding the facts. 0.69 0.06
II 16. I was frustrated with the client for being reneged on my support plans. 0.67 0.05
II 14. I was confused by the clients who refused the support I suggested. 0.65 0.00
II 18. I was confused by the client's negative reaction to support. 0.59 0.03
I 2. I was depressed about clients who complained for long periods. −0.06 0.86 0.89 0.56
I 1. I was scared of clients who reprimanded me in a loud voice. −0.15 0.84
I 4. I felt confused by the client's baseless blame. 0.02 0.81
I 10. I was scared of the client who seemed aroused. −0.03 0.78
I 5. I was confused by the client's unexpected complaint. −0.01 0.78
I 6. I was frustrated with clients making difficult requests. 0.23 0.61
I 7. I was confused by clients who complained of mental instability. 0.27 0.43
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Note: Maximum‐likelihood method with promax rotation were used. Factor 1 (conceptual flamework II): ‘negative emotions toward aggressive and emotional attitudes’. Factor 2 (conceptual flamework I): ‘negative emotions toward rejecting and uncooperative attitudes’. Correlation between Factor 1 and Factor 2: 0.35. Cronbach α: 0.89, Spearman‐Brown reliability coefficient = 0.92. The bold values indicates that these items belong to that dimension.

FIGURE 3.

FIGURE 3

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Confirmatory factor analysis (n = 385). GFI: 0.924, AGFI: 0.890, CFI: 0.952, RMSEA: 0.07. [Colour figure can be viewed at wileyonlinelibrary.com]

4.3.5. Results for Convergent, Discriminant Validity and Criterion‐Related Validity

Details of the convergent validity and criterion‐related validity assessments are presented in Table 5. The Spearman's r coefficients between the total scale, factor 1, factor 2 and PANAS were significant correlations: 0.22, 0.24 and 0.12, respectively. The Spearman's r coefficients between the total scale, factor 1, factor 2, and the PHN's difficulty in support were significant correlations: 0.49, 0.41 and 0.38, respectively. Spearman's r coefficients between the total scale, factor 1, factor 2, and the number of times negative attitudes were reported were significant correlations: 0.29, 0.32 and 0.15, respectively. Spearman's r coefficients between the total scale, factor 1, factor 2, and the types of behaviours exhibited by parents were significant correlations: 0.52, 0.46 and 0.40, respectively. AVE exceeded 0.50 and the square of the factor correlations.

TABLE 5.

Convergent validity and criterion‐related validity.

Index Scale item
Factor 1 Factor 2 All scale
PANAS‐negative 0.24** 0.12* 0.22**
PHNs' difficulty in support 0.41** 0.38** 0.49**
Number of times negative attitudes were reported 0.32** 0.15** 0.29**
the types of behaviours exhibited by parents 0.46** 0.40** 0.52**
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Note: Spearman correlation.

*

p < 0.05.

**

p < 0.01.

4.3.6. Results for Reliability

The scale demonstrated an acceptable internal consistency reliability. Cronbach α was 0.89 for the whole scale, 0.89 for factor 1 and 0.90 for factor 2. The value of the Spearman‐Brown reliability coefficient was 0.92 (Table 4).

5. Discussion

This study aimed to address the gap in measuring PHNs' emotional burden in child abuse prevention by developing a reliable and valid negative emotions scale specifically tailored to their community‐based practice. The scale was constructed through a multi‐phase process involving item generation (phase 1), interviews with PHNs (phase 2), a pilot survey (phase 3) and a main survey (phase 4). The findings confirmed the scale's acceptable psychometric properties, contributing to the advancement of negative emotion and emotional labour research in public health nursing.

5.1. Characteristics of Participants

In the main survey, sampling was started based on the municipality's size. The number of participating municipalities was 189 (large city: 18, medium‐sized city: 71, and town and village: 100). These numbers were comparable to those of the previous study (Yoshioka‐Maeda et al. 2023). This reflects a certain degree of representation of municipalities in Japan. The response rate was 48.5, which is higher than that reported in other studies on PHNs (Okamoto et al. 2022). Furthermore, the participants' gender and experiences as PHNs were comparable to those of previous studies (Arimoto and Tadaka 2021), suggesting that this study ensured a certain degree of representation of PHNs in Japan.

5.2. Reliability and Validity of the Scales

The results show that the scale has adequate reliability and validity and is a useful structure for referring to guidelines for scale development (Boateng et al. 2018). Cronbach α was ≥ 0.80 for the scale and for the two factors, indicating high internal consistency; additionally, the Spearman‐Brown reliability coefficient was 0.95, supporting split‐half reliability. The Spearman‐Brown reliability coefficient was 0.95. The draft items were modified based on the results of interviews with PHNs, pilot surveys and the main survey. To ensure content validity, items were developed from the theoretical framework of emotional labour and refined through PHN interviews and iterative survey testing. Although emotional labour is an important concept in discussing negative emotions, no scale has been developed based on this concept. Therefore, this scale ensures reliability and content validity to evaluate PHNs' negative emotions.

In the item and exploratory factor analyses, a two‐factor, 15‐item scale was created by selecting items based on the factor loadings. Covariance was added to the six‐item sets of error variables according to the modification index values. The contents of these two factors are the same as those in the first conceptual framework. Six‐item sets of variables were based on the similarity of situations in which negative emotions were experienced. The model fit was generally good. These results confirm the construct validity of the scale.

Convergent validity and criterion‐based validity analyses showed significant correlations with PANAS, PHNs' difficulty in providing support, frequency of negative attitudes reported and parental behaviours, suggesting that the scale captures meaningful emotional responses in practice. Regarding discriminant validity, the AVE was higher than the square of the factor correlations, indicating that the two factors measure distinct but related constructs. These results confirm the convergent, criterion‐based and discriminant validity of the scale.

5.3. Usefulness of the Scale in Child Abuse Prevention Practice

Developing a negative emotion scale made it possible to assess the psychological burden experienced by PHNs in child abuse prevention activities. This scale was developed for professionals responsible for child abuse prevention in community settings. In Japan, it was designed for PHNs, but other nursing professionals overseas may be able to utilise it. This scale can be used to minimise the negative effects of negative emotions. For example, because it visualises the negative emotions experienced by PHNs when facing challenging cases, the scale can be used to identify areas of support systems that need to be strengthened. Incorporating these findings into PHN training programs—even at the basic education stage—could help future PHNs recognise that experiencing negative emotions is normal and learn coping strategies, thereby preventing burnout and reducing turnover.

Moreover, this scale can be used in future studies to examine the impact of negative emotions on child abuse prevention. The correlation between factor 1 and factor 2 was low, although significant at 0.35. Previous studies have examined the association of variables with each subscale of negative emotions rather than the total score in hospital settings. Situations in which the subscales ‘aggressive and emotional attitude’ and ‘rejective and uncooperative attitude’ may not occur at the same time exist. When using this scale, each subscale must be used separately. Furthermore, a short version of the scale needs to be developed so that the results can be easily evaluated by PHNs.

5.4. Strengths and Limitations of the Study and Recommendations for Future Research

This study has five limitations. The first is sampling bias. Municipalities and PHNs interested in child abuse may have also participated in this study. PHNs who suffer from negative emotions may not have participated in this study. Although the response rate for the main survey was high (48.5%), only 385 of the 1132 distributed questionnaires were included in the final analysis, which is a limitation. Nevertheless, this sample size was sufficient to examine the validity of the scale. The wide range of scores on the scale minimised the possibility of bias in the distribution of scores owing to the limited number of participants in the study. Second, owing to the burden of participant responses and the possibility of a response rate, the test–retest reliability was not examined. Also, inter‐rater reliability was not examined because this scale measures personal experience. Third, there may be discrepancies between the timing of the emotional experience and the scale response. Although retrospective self‐reporting is common in emotion research, recall bias remains a concern. Fourth, items on the scale were generated by combining experiences and emotions. Although this adjustment makes it easier to recall specific events, it may also be difficult to respond to the scale, as PHNs' experiences and emotions do not match. However, the scale was validated through interviews to minimise this problem. Last, the negative emotion scale may have created a social desirability bias owing to guilt over negative emotions. In this study, responses were anonymous and voluntary.

The effects of negative emotions, decreased quality of support and psychological effects, such as burnout, are evident among hospital nurses but not among PHNs (Szczygiel and Mikolajczak 2018). This study made it possible to assess negative emotions among PHNs, and their negative effects need to be investigated in future research.

6. Conclusion

This study developed and validated a negative emotions scale for PHNs engaged in child abuse prevention, addressing a critical measurement gap in public health nursing. The final version consists of 15 items across two subscales: ‘negative emotions toward aggressive and emotional attitudes’ and ‘negative emotions toward rejecting and uncooperative attitudes.’ This tool offers a practical and theoretically grounded means to advance research and practice supporting PHNs in their emotionally demanding roles related to child abuse prevention. The scale demonstrated acceptable reliability and content, construct, convergent, criterion‐related and discriminant validity. This tool offers a practical and theoretically grounded means to advance research and practice supporting PHNs in their emotionally demanding roles related to child abuse prevention.

Author Contributions

Haruka Yokobori conceptualised the idea, collected data for the study design, survey, analysed the data and wrote the manuscript. Chikako Honda, Hiroshige Matsumoto and Akari Maeda‐Suzuki contributed to interpreting the data and reviewing the manuscript. Kyoko Yoshioka‐Maeda contributed to interpreting the data, reviewing the manuscript and supervising all the surveys.

Disclosure

Statistics: The authors affirmed that the methods used in the data analyses are suitably applied to their data within their study design and context, and the statistical findings have been implemented and interpreted correctly. Additionally, the authors agreed to take responsibility for ensuring that the choice of statistical approach was appropriate and was conducted and interpreted correctly as a condition to submit to the Journal.

Permission to Reproduce Material From Other Sources: Our study uses previously published material within the limits of fair use for research purposes. All citations are correctly attributed, and no content exceeds the permissible extent as defined by copyright regulations.

Ethics Statement

The ethics review committee of the primary investigator approved the study protocol, which adhered to the Declaration of Helsinki (no. 2023281NI, 29 December 2023; 2023281NI‐(1), 21 February 2024; 2023281NI‐(2), 12 June 2024).

Consent

Informed consent was obtained from all the participants.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Appendix S1: jocn70128‐sup‐0001‐AppendicesS1‐S3.zip.

JOCN-35-1620-s001.zip (29.6KB, zip)

Acknowledgements

We appreciate all participants, municipal management supporting this study. We thank Dr. Riho MOTEGI (Department of Public Health Nursing, International University of Health and Welfare), Dr. Noriko HOSOYA (Department of Nursing, Chiba Prefectural University of Health Sciences) and Yasuhiro HAGIWARA (Department of Biostatistics, The University of Tokyo) for their kind assistance in data collection and analysis. The Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising From Their Utilisation to the Convention on Biological Diversity. This study is a cross‐sectional study using a questionnaire, and it is not applicable.

Funding: This work was supported by the Yamaji Fumiko Nursing Research Fund.

Data Availability Statement

Research data are not publicly shared because of privacy restrictions.

References

  1. Acquadro Maran, D. , Varetto A., Zedda M., and Magnavita N.. 2018. “Workplace Violence Toward Hospital Staff and Volunteers: A Survey of an Italian Sample.” Journal of Aggression, Maltreatment and Trauma 27, no. 1: 76–95. 10.1080/10926771.2017.1405314. [DOI] [Google Scholar]
  2. Arimoto, A. , and Tadaka E.. 2021. “Developing and Validating a New Scale to Assess Signs of Neglect of Infants and Caregivers.” Journal of Interpersonal Violence 36, no. 19–20: 8960–8983. 10.1177/0886260519863724. [DOI] [PubMed] [Google Scholar]
  3. Bailey, J. , Martin S. A., and Bangs A.. 2023. “Managing Difficult Patient Encounters.” American Family Physician 108, no. 5: 494–500. 10.12788/cp.0144. [DOI] [PubMed] [Google Scholar]
  4. Bedyńska, S. , and Żołnierczyk‐Zreda D.. 2015. “Stereotype Threat as a Determinant of Burnout or Work Engagement. Mediating Role of Positive and Negative Emotions.” International Journal of Occupational Safety and Ergonomics 21, no. 1: 1–8. 10.1080/10803548.2015.1017939. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Boateng, G. O. , Neilands T. B., Frongillo E. A., Melgar‐Quiñonez H. R., and Young S. L.. 2018. “Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer.” Frontiers in Public Health 6: 1–18. 10.3389/fpubh.2018.00149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Campana, K. L. , and Hammoud S.. 2015. “Incivility From Patients and Their Families: Can Organisational Justice Protect Nurses From Burnout?” Journal of Nursing Management 23, no. 6: 716–725. 10.1111/jonm.12201. [DOI] [PubMed] [Google Scholar]
  7. Chi, N. W. , Yang J., and Lin C. Y.. 2018. “Service Workers' Chain Reactions to Daily Customer Mistreatment: Behavioral Linkages, Mechanisms, and Boundary Conditions.” Journal of Occupational Health Psychology 23, no. 1: 58–70. 10.1037/ocp0000050. [DOI] [PubMed] [Google Scholar]
  8. Diefendorff, J. M. , Richard E. M., and Yang J.. 2008. “Linking Emotion Regulation Strategies to Affective Events and Negative Emotions at Work.” Journal of Vocational Behavior 73, no. 3: 498–508. 10.1016/j.jvb.2008.09.006. [DOI] [Google Scholar]
  9. Dmytryshyn, A. L. , Jack S. M., Ballantyne M., Wahoush O., and MacMillan H. L.. 2015. “Long‐Term Home Visiting With Vulnerable Young Mothers: An Interpretive Description of the Impact on Public Health Nurses.” BMC Nursing 14, no. 1: 1–14. 10.1186/s12912-015-0061-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Eker, H. H. , Özder A., Tokaç M., Topçu I., and Tabu A.. 2012. “Aggression and Violence Towards Health Care Providers, and Effects Thereof.” Archives of Psychiatry and Psychotherapy 14, no. 4: 19–29. [Google Scholar]
  11. Enders, C. K. 2010. Applied Missing Data Analysis. Guilford Press. [Google Scholar]
  12. Fornell, C. , and Larcker D. F.. 1981. “Structural Equation Models With Unobservable Variables and Measurement Error: Algebra and Statistics.” Journal of Marketing Research 18: 382–389. [Google Scholar]
  13. Georgia, M. , and Richard P. H.. 1998. “Learning Disability Care Staff's Emotional Reactions to Aggressive Challenging Behaviors: Development of a Measurement Tool.” British Journal of Clinical IPsychology 37: 441–449. 10.1016/j.jaci.2012.05.050. [DOI] [PubMed] [Google Scholar]
  14. Goussinsky, R. 2020. “The Moderating Role of Rumination and Social Sharing in the Relationship Between Mistreatment and Service Sabotage and Depersonalization: A Cross‐Sectional Study of Hospital Nurses.” International Journal of Nursing Studies 110: 1–9. 10.1016/j.ijnurstu.2020.103705. [DOI] [PubMed] [Google Scholar]
  15. Goussinsky, R. , and Livne Y.. 2016. “Coping With Interpersonal Mistreatment: The Role of Emotion Regulation Strategies and Supervisor Support.” Journal of Nursing Management 24, no. 8: 1109–1118. 10.1111/jonm.12415. [DOI] [PubMed] [Google Scholar]
  16. Grandey, A. A. 2000. “Emotional Regulation in the Workplace: A New Way to Conceptualize Emotional Labor Emotion Regulation in the Workplace: A New Way to Conceptualize Emotional Labor.” Journal of Occuational Health Psychology 5, no. 1: 95–110. 10.1037//1076-8998.S.1.9S. [DOI] [PubMed] [Google Scholar]
  17. Grandey, A. A. , Foo S. C., Groth M., and Goodwin R. E.. 2013. “Free to Be You and Me: A Climate of Authenticity Alleviates Burnout From Emotional Labor.” Journal of Occupational Health Psychology 17, no. 1: 1–14. 10.1037/a0025102. [DOI] [PubMed] [Google Scholar]
  18. Hemingway, A. , Aarts C., Koskinen L., Campbell B., and Chassé F.. 2013. “A European Union and Canadian Review of Public Health Nursing Preparation and Practice.” Public Health Nursing 30, no. 1: 58–69. 10.1111/j.1525-1446.2012.01048.x. [DOI] [PubMed] [Google Scholar]
  19. Hochschild, A. R. 1983. The Managed Heart: Commercialisations of Human Feeling. University of California Press. [Google Scholar]
  20. Honda, J. , Sasaki A., Tsuda S., Matsuyama M., and Morita K.. 2023. “Aspects of Emotional Labor of Public Health Nurses Engaged in Interpersonal Support.” Nursing Open 10, no. 2: 1048–1059. 10.1002/nop2.1372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Jack, S. M. , Gonzalez A., Marcellus L., et al. 2021. “Public Health Nurses' Professional Practices to Prevent, Recognize, and Respond to Suspected Child Maltreatment in Home Visiting: An Interpretive Descriptive Study.” Global Qualitative Nursing Research 8: 2333393621993450. 10.1177/2333393621993450. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kageyama, M. , and Yokoyama K.. 2018. “Child‐Rearing Support Provided by Public Health Nurses to People With Mental Illness: Qualitative Descriptive Study.” Open Nursing Journal 12, no. 1: 162–170. 10.2174/1874434601812010162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kline, P. 1994. “An Easy Guide to Factor Analysis.” In An Easy Guide to Factor Analysis. Routledge. 10.4324/9781315788135. [DOI] [Google Scholar]
  24. Kuruppu, J. , Humphreys C., McKibbin G., and Hegarty K.. 2022. “Tensions in the Therapeutic Relationship: Emotional Labour in the Response to Child Abuse and Neglect in Primary Healthcare.” BMC Primary Care 23, no. 1: 1–13. 10.1186/s12875-022-01661-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. LanctÔt, N. , and Guay S.. 2014. “The Aftermath of Workplace Violence Among Healthcare Workers: A Systematic Literature Review of the Consequences.” Aggression and Violent Behavior 19, no. 5: 492–501. 10.1016/j.avb.2014.07.010. [DOI] [Google Scholar]
  26. Leonard, R. , Linden M., and Grant A.. 2020. “Predictors of Family Focused Practice Among Health Visitors: A Mixed Methods Study.” Journal of Advanced Nursing 76, no. 5: 1255–1265. 10.1111/jan.14310. [DOI] [PubMed] [Google Scholar]
  27. Lin, M. C. 2020. “Communication Neglect, Caregiver Anger and Hostility, and Perceptions of Older Care Receivers' Cognitive Status and Problem Behaviors in Explaining Elder Abuse.” Journal of Elder Abuse & Neglect 32, no. 3: 235–258. 10.1080/08946566.2020.1741054. [DOI] [PubMed] [Google Scholar]
  28. Martin, E. B. , Mazzola N. M., Brandano J., Luff D., Zurakowski D., and Meyer E. C.. 2015. “Clinicians' Recognition and Management of Emotions During Difficult Healthcare Conversations.” Patient Education and Counseling 98, no. 10: 1248–1254. 10.1016/j.pec.2015.07.031. [DOI] [PubMed] [Google Scholar]
  29. Okamoto, R. , Kiya M., Koide K., Tanaka M., and Kageyama M.. 2022. “Cases of Intervention Refusal Encountered by Public Health Nurses in Japan and Characteristics of Their Support–Qualitative Analysis of Described Mother‐Child and Elderly Cases.” BMC Nursing 21, no. 1: 1–9. 10.1186/s12912-021-00706-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Olds, D. L. , Kitzman H., Anson E., et al. 2019. “Prenatal and Infancy Nurse Home Visiting Effects on Mothers: 18‐Year Follow‐Up of a Randomized Trial.” Pediatrics 144, no. 6: e20183889. 10.1542/peds.2018-3889. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Rossi, M. F. , Beccia F., Cittadini F., et al. 2023. “Workplace Violence Against Healthcare Workers: An Umbrella Review of Systematic Reviews and Meta‐Analyses.” Public Health 221: 50–59. 10.1016/j.puhe.2023.05.021. [DOI] [PubMed] [Google Scholar]
  32. Sato, A. , and Yasuda A.. 2001. “Development of the Japanese Version of Positive and Negative Affect Schodule (PANAS) Scale.” Japanese Journal of Personality 9, no. 2: 138–139. [Google Scholar]
  33. Statistics Bureau . 2025. “Ministry of Internal Affairs and Communications. Social Security, Tables.” 23. https://www.stat.go.jp/english/data/nenkan/74nenkan/1431‐23.html.
  34. Szczygiel, D. D. , and Mikolajczak M.. 2018. “Emotional Intelligence Buffers the Effects of Negative Emotions on Job Burnout in Nursing.” Frontiers in Psychology 9: 1–10. 10.3389/fpsyg.2018.02649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Taylor, J. , Smith P., and Taylor J.. 2017. “A Hermeneutic Phenomenological Study Exploring the Experience Health Practitioners Have When Working With Families to Safeguard Children and the Invisibility of the Emotions Work Involved.” Journal of Clinical Nursing 26, no. 3–4: 557–567. 10.1111/jocn.13486. [DOI] [PubMed] [Google Scholar]
  36. ten Hoeve, Y. , Brouwer J., and Kunnen S.. 2020. “Turnover Prevention: The Direct and Indirect Association Between Organizational Job Stressors, Negative Emotions and Professional Commitment in Novice Nurses.” Journal of Advanced Nursing 76, no. 3: 836–845. 10.1111/jan.14281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Viotti, S. , Gilardi S., Guglielmetti C., and Converso D.. 2015. “Verbal Aggression From Care Recipients as a Risk Factor Among Nursing Staff: A Study on Burnout in the JD‐R Model Perspective.” BioMed Research International 2015: 1–17. 10.1155/2015/215267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. von Elm, E. , Altman D. G., Egger M., Pocock S. J., Gøtzsche P. C., and Vandenbroucke J. P.. 2015. “Annals of Internal Medicine Academia and Clinic the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting.” Annals of Internal Medicine 147, no. 8: 573–578. [DOI] [PubMed] [Google Scholar]
  39. Wang, M. , Liao H., Zhan Y., and Shi J.. 2011. “Daily Customer Mistreatment and Employee Sabotage Against Customers: Examining Emotion and Resource Perspectives.” Academy of Management Journal 54, no. 2: 312–334. 10.5465/AMJ.2011.60263093. [DOI] [Google Scholar]
  40. Watson, D. , Clark L. A., and Tellegen A.. 1988. “Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales.” Journal of Personality and Social Psychology 54, no. 6: 1063–1070. [DOI] [PubMed] [Google Scholar]
  41. World Health Organization . 2020. Global Status Report on Preventing Violence Against Children 2020. World Health Organization. https://apps.who.int/iris/bitstream/handle/10665/332394/9789240004191‐eng.pdf%0Ahttps://www.who.int/publications‐detail‐redirect/9789240004191. [Google Scholar]
  42. Wu, Y. , Ahaus K., Shi J., Zhao D., and Buljac‐Samardzic M.. 2025. “Perspectives of Physicians on Risk Factors for Patient Aggression and Violence Against Physicians in Chinese Hospitals: A Q‐Methodology Study.” Human Resources for Health 23, no. 1: 5. 10.1186/s12960-025-00976-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Yokobori, H. , Iwasaki‐Motegi R., Naruse T., and Yamamoto‐Mitani N.. 2022. “Public Health Nurses' Activities Toward Child Abuse Prevention Before Childbirth in Japan.” Public Health Nursing 39: 1346–1354. 10.1111/phn.13122. [DOI] [PubMed] [Google Scholar]
  44. Yoshioka‐Maeda, K. , and Fujii H.. 2022. “Mothers Susceptible to Child Maltreatment and Requiring Public Health Nurses' Continuous Support.” Public Health Nursing 39, no. 1: 48–61. 10.1111/phn.13004. [DOI] [PubMed] [Google Scholar]
  45. Yoshioka‐Maeda, K. , Matsumoto H., Inagaki‐Asano A., and Honda C.. 2023. “Community‐Based Hip Screening for up to Four‐Month‐Old Infants and Health Guidance for Their Caregivers in Japan: A Nation‐Wide Survey.” Nursing Reports 13, no. 4: 1442–1451. 10.3390/nursrep13040121. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix S1: jocn70128‐sup‐0001‐AppendicesS1‐S3.zip.

JOCN-35-1620-s001.zip (29.6KB, zip)

Data Availability Statement

Research data are not publicly shared because of privacy restrictions.

Articles from Journal of Clinical Nursing are provided here courtesy of Wiley

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