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. Author manuscript; available in PMC: 2023 Aug 1.
Published in final edited form as: J Adv Nurs. 2022 Feb 17;78(8):2460–2471. doi: 10.1111/jan.15176

Advanced practice nurse work environments and job satisfaction and intent to leave: Six-state cross sectional and observational study

Lusine Poghosyan 1,2, Supakorn Kueakomoldej 3, Jianfang Liu 3, Grant Martsolf 4
PMCID: PMC9283202  NIHMSID: NIHMS1773992  PMID: 35174905

Abstract

Aims:

To explore the relationship between nurse practitioner work environment and nurse practitioner outcomes (job satisfaction and intent to leave) in the United States.

Design:

The study used a cross-sectional survey design to collect survey data from primary care nurse practitioners in six states in the United States.

Methods:

We sent mail surveys to 5689 eligible nurse practitioners in Arizona, New Jersey, Washington, Pennsylvania, California and Texas. The mail also contained an online link. Participants could complete either the paper or online questionnaire. In total, 1244 participants completed the survey in 2018–2019. The work environment was measured using the Nurse Practitioner-Primary Care Organizational Climate Questionnaire comprised of four subscales: Nurse Practitioner-Administration Relations, Nurse Practitioner-Physician Relations, Independent Practice and Support and Professional Visibility. Global items measured job satisfaction and intent to leave. We used mixed-effect proportional-odds cumulative logit models to assess the association between work environment and job satisfaction and intent to leave.

Results:

Overall, 90% of participants were either very satisfied or somewhat satisfied with their job and 22% reported intent to leave their job in 1 year. With a one-unit increase in the organizational-level Nurse Practitioner-Administration Relations score, the odds of having a higher job satisfaction level increased by about four times and the odds of intent to leave job decreased by about 60%. A higher organizational-level Nurse Practitioner-Physician Relations score was significantly associated with higher job satisfaction and lower odds of intent to leave.

Conclusion:

Improvements in work environments may improve nurse practitioner job satisfaction and retention.

Impact:

This study examined the relationship between work environment, job satisfaction and turnover intention of nurse practitioners. Better work environment is associated with higher job satisfaction and lower turnover intention. Findings have implications for clinical leadership who can take actions to create better work environments to increase the nurse practitioner workforce capacity.

Keywords: intent to leave, job satisfaction, nurse practitioners, work environment

1 ∣. INTRODUCTION

Due to an ageing population, increasing prevalence of chronic conditions and workforce shortages, the United States healthcare system faces challenges meeting the growing demand for primary care. Almost 80 million Americans live in health professional shortage areas (Health Resources & Services Administration, 2019). To meet the demand for primary care, significant efforts are implemented to increase the capacity of the healthcare workforce. One important strategy includes increasing the utilization of the advanced practice nurses (APNs), specifically nurse practitioners (NPs) (Buerhaus, 2018). Internationally, many definitions of APNs exist; the most common refers to nurses working in roles beyond the scope of practice of a registered nurse and have received additional training (Maier & Aiken, 2016). In many countries—including the United States, the United Kingdom, and the Netherlands, Thailand and Singapore (Ladd & Schober, 2018; Maier & Aiken, 2016)—established educational programs train nurses at Master's and Doctoral level to become APNs such as NPs, and their scope of practice is expanded to include making treatment decisions and referrals, prescribing medications and ordering tests among other functions. In other countries such as France and Germany, the APN role is in its early stages. While Master's and Doctoral programs have been established, the scope of practice is expanded only for some pilot projects (Germany) or for specific functions only, such as prescribing (France) (Maier et al., 2017). Despite inconsistencies, the uptake of APNs internationally is growing, and policies are being designed to shift tasks from physicians to APNs and expand APN scope of practice as an effective strategy to increase primary care capacity (Maier & Aiken, 2016). Across many countries, policy, regulatory and educational reforms are being designed to strengthen APN workforce and expand their scope of practice to ensure patients have access to high quality primary care services.

The APN workforce plays a critical role in the U.S. healthcare system. APNs are registered nurses with Masters or Doctoral level education and training in caring for specific patient populations. NPs, certified registered nurse anaesthetists, nurse-midwives and clinical nurse specialists comprise the APN workforce with NPs being the largest group. The NP workforce is projected to increase by 93% between 2013 and 2025 (U.S. Department of Health and Human Services, Health Resources and Services Administration, Bureau of Health Workforce & National Center for Health Workforce Analysis, 2017). Many studies show that the care NPs provide is of similar quality to primary care physicians and improves patient outcomes (Kurtzman & Barnow, 2017; Perloff et al., 2016). Thus, this growing workforce both in the United States and internationally can play a critical role in meeting the demand for healthcare services.

However, many barriers affect the optimal utilization of the NP workforce that may limit their contributions to healthcare systems globally. For example, while NPs in the U.S. must pass standardized national certification exams, there are variable scope of practice (SOP) regulations governing NP practice across the states, which determine the care and the services NPs can provide to patients (Buerhaus, 2018). These SOP regulations fall under the following categories: full, reduced, and restricted. Full SOP allows NPs to independently deliver care and prescribe medications to patients without physician involvement; reduced SOP requires NPs to collaborate with physicians; and restricted SOP requires NPs to be supervised by physicians to deliver the same care.

In addition, poor NP work environment in the employment setting of these clinicians, characterized by a lack of support and resources, poor relations with administration, role ambiguity, or limited involvement in organizational decisions (Poghosyan et al., 2013) affect NPs' ability to deliver care and predispose NPs to negative outcomes including job dissatisfaction and intent to leave (Faraz, 2017; Poghosyan, Liu, et al., 2017). Dissatisfied clinicians may leave their jobs at higher rates, and high turnover will deplete valuable workforce resources in healthcare organizations and further challenge the delivery of safe care. Turnover in primary care practices also adversely affects patients' care experiences (Reddy et al., 2015) and increased patients' emergency care use and health spending (Sabety et al., 2021).

While the APN workforce is growing globally, knowledge about this workforce and about their outcomes are still limited. To date, little is known about primary care NP job satisfaction and intent to leave their job and how varying levels of SOP regulations and work environments may predispose them to negative outcomes. Our study aims to examine the relationship between work environment, varying levels of SOP and workforce outcomes of NPs in the United States. Studying the United States NP workforce with varied state SOP regulations produces important insight about the potential impact of policy and work environment for NPs in other countries. Creating favourable policies and work environments is beneficial for clinicians globally, and the findings of this study will have important implications not only for NP practice in the United States, but also in other countries that are beginning to employ APNs in roles similar to NPs in the United States but with varying regulations and organizational structures.

1.1 ∣. Background

Despite the importance of NPs to increasing the global primary care capacity, literature that examine NP workforce outcomes are limited. Among other healthcare professionals, a salient predictor of clinician workforce outcomes is their work environment (Abraham et al., 2020; Nantsupawat et al., 2017; Paguio et al., 2020). Work environment has been defined as practice characteristics that may promote or restrict optimal nursing practice (Lake, 2002). Previous nurse studies demonstrated that supportive work environments are associated with improved clinician and patient outcomes (Nantsupawat et al., 2017; Olds et al., 2017). However, unlike other professions, NPs face unique challenges of restricted practice due to variability of SOP policies. SOP policies are related to NPs' practice autonomy (Park et al., 2018), which has frequently been cited as predictor of NP job satisfaction and turnover intention (Han et al., 2018). Both NP work environment and SOP polices may influence NP turnover intention and job satisfaction. Therefore, we hypothesize that both work environment and SOP policies are associated with NPs' job satisfaction and turnover intention.

To test our hypothesis, we are guided by an adapted National Academy of Medicine's (NAM) systems model of clinician burnout and professional well-being (National Academies of Sciences, Engineering, & Medicine, 2019). The model was originally created to address health care clinician burnout and professional well-being, which NAM defined to include engagement, quality of life and satisfaction at work (Chari et al., 2018; National Academies of Sciences, Engineering, & Medicine, 2019). This model posits that levels of health systems (e.g. policy, management and organizational level) interact together to influence work system factors, which predict professional well-being. Work system factors contain two dimensions: demands (e.g. excessive workload, inadequate staffing) and resources (e.g. organizational culture and relationships). In our study, professional wellbeing is operationalized as NPs' job satisfaction and turnover intention. State SOP represents a system variable at the policy level and NP work environment represents the job resources dimension of work system factors (i.e. NP visibility, relationship with physician and administrations and autonomous practice). According to the model, individual clinician factors such age, gender, personality and social support may intervene in the relationship between systems and professional well-being. We will include NP demographic factors (e.g. age, gender) as control variables.

2 ∣. THE STUDY

2.1 ∣. Aims

The aim of the study was to investigate the relationship between NP work environment, SOP policies and NP job satisfaction and intent to leave in six U.S. states.

2.2 ∣. Design

The study used a cross-sectional observational design to collect data from primary care NPs at one point in time. The study setting included the following six U.S. states: Arizona (AZ), California (CA), New Jersey (NJ), Pennsylvania (PA), Texas (TX) and Washington (WA). These states were selected because they have different state SOP regulations governing NP practice. AZ and WA represent full SOP states, NJ and PA represent reduced SOP states, and CA and TX represent restricted SOP states. We have also selected these states because of their geographic and population diversity. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines and checklist was followed (see Appendix S1).

2.3 ∣. Participants

We used the SK&A database to identify primary care NPs (DesRoches et al., 2015). This database contains information on ambulatory care providers in the United States. To identify primary care NPs, we retained all primary care practices in the selected states which we defined as any practice in which the majority of physicians had a primary care specialty. The database did not have information about practices that only employed NPs. We selected practices that had at least one NP and extracted contact information for all NPs in AZ, NJ and WA, a 75% random sample for PA, and a 50% random sample for CA and TX given the large number of NPs in these states. Random samples ensured similar counts of NPs by state. We also called each of the potential respondents to confirm that the address reported through SK&A was valid, the practice was truly primary care, and the NP worked at the practice. The final sample consisted of 5,209 NPs.

2.4 ∣. Data collection

A professional survey organization conducted the data collection. A cover letter describing the study, the paper questionnaire and questionnaire's online link with a unique identification for each NP were mailed to NPs. NPs could complete either a paper or online survey. Following a modified Dillman process for mixed-mode surveys to achieve maximum response rate (Dillman et al., 2009), a postcard reminder was sent to non-respondents 2 weeks after the initial mailing and then we conducted the second mailing to non-respondents 2 weeks after the postcard reminder. In total, three surveys and two postcard reminders 2 weeks apart were sent to NPs. All mailings included an online link which allowed participants to complete the survey online at their convenience. After the last attempt, NPs who did not complete the survey were contacted by phone. Three phone reminders were made to each NP. The data collection took place in 2018–2019. More details about the study methodology have been previously published (Harrison et al., 2021).

2.5 ∣. Variables

2.5.1 ∣. Main explanatory variables

Our main explanatory variables are state SOP polices and organizational-level NP work environment. For SOP level, we used a three-level categorical variable to indicate the SOP policy in each state (1 = full SOP, 2 = reduced SOP and 3 = restricted SOP). NP work environment was measured by the Nurse Practitioner-Primary Care Organizational Climate Questionnaire (NP-PCOCQ) (Poghosyan, Nannini, Finkelstein, et al., 2013). The development of NP-PCOCQ was based on existing evidence and conceptual models, and the tool went through rigorous psychometric evaluations (Poghosyan et al., 2019; Poghosyan, Chaplin, & Shaffer, 2017; Poghosyan, Nannini, & Clarke, 2013; Poghosyan, Nannini, Finkelstein, et al., 2013). The NP-PCOCQ has strong psychometric properties with acceptable internal consistency, construct, discriminant and predictive validity (Poghosyan, Nannini, Finkelstein, et al., 2013). The tool contains 29 items asking NPs to rate the degree to which certain characteristics are present in their organizations using a 4-point Likert-like scale from ‘strongly agree’ (1) to ‘strongly disagree’ (4). Higher scores on each item indicate a better work environment. The tool contains four subscales: NP-Administration Relations (NP-AR), NP-Physician Relations (NP-PR), Independent Practice and Support (IPS) and Professional Visibility (PV). NP-administration relationship is a critical aspect of NP work environment (Poghosyan, Nannini, & Clarke, 2013) that focuses on collaboration and communication between NPs and administrators, and the NP-AR subscale with its nine items measures this domain. The NP-PR subscale has seven items measuring the relationship, communication and teamwork between NPs and physicians. The IPS subscale, which contains nine items, measures resources and support NPs have for their independent practice. Finally, the PV subscale has four items measuring how visible NP role is in the organization. The work environment measures were collected at the individual NP level and aggregated to the organization level. We first computed individual-level mean scores on each subscale for respondents if more than 70% of the subscale items were non-missing (Downey & King, 1998), and then computed organizational-level mean scores on each subscale by aggregating the responses of all NPs in the same practice. Higher mean scores on each subscale indicate better work environment. The mean scores on these four subscales were included as the explanatory variables.

2.5.2 ∣. Outcome variables

The main outcome variables included job satisfaction and intent to leave. The job satisfaction measure was derived from NP responses to a single item which asked how satisfied they were with their present job and was measured on a 4-point scale ranging from ‘very satisfied’ (1) to ‘very dissatisfied’ (4). To ease interpretation, we reverse coded this variable (i.e. higher score indicates higher job satisfaction) for analysis. Global job satisfaction items have been used in research and have been shown to be effective measures (Wanous et al., 1997). The intent to leave job measure was derived from responses to a single item which probed how likely they were to leave their current position in the next year and was measured on a 4-point scale ranging from ‘very likely’ (1) to ‘very unlikely’ (4). The item has been extensively used in past research of nurses (Nantsupawat et al., 2017; Poghosyan, Liu, et al., 2017).

2.5.3 ∣. Covariates

The questionnaire also included measures of demographics (e.g. age, sex, race and education) and organizational characteristics such as practice setting (e.g. whether they work in a physician's office, community health centre or hospital-based clinic), length of time in current primary position, hours worked per week over the last month in their primary position and number of other NPs in their organization.

2.6 ∣. Ethical considerations

The study protocol received ethics approval by a university institutional review board.

2.7 ∣. Data analysis

We computed descriptive statistics to characterize the overall sample and respondents by state SOP status. Frequency analysis of the outcome measures were computed by SOP status and overall sample. Then, we examined the association between the four organizational-level NP-PCOCQ subscales and job satisfaction and intent to leave. We assessed the multicollinearity between explanatory variables using variance inflation factor: values higher than 5, a commonly used threshold, indicate high multicollinearity (Kock & Lynn, 2012). Effects of potential covariates (i.e. age, sex, race, hours work per week, years working as NP and number of NPs in the practice, clinic type) were controlled in the final multivariable regression models. We used proportional-odds cumulative logit models for both outcome measures as they were measured on a 4-point Likert scale. Mixed-effect models were fitted to account for the hierarchical design of the data, where 1,244 participants (Level 1) were nested in 1,109 practices (Level 2). Adjusted cumulative odds ratio (OR) and associated 95% confidence intervals (CIs) were reported for assessing the direction and strength of the associations. Data analysis was conducted in SAS 9.4 (SAS Institute Inc., 2013). Patterns of missing data were assessed, and there was no pattern of missing data for key demographic variables, NP-PCOCQ subscale scores and outcomes. The amount of missing data were about 5% for responses with outcome values. Thus, list wise deletion was used in final mixed-effect regression models. We performed sensitivity analyses using mixed-effect linear regression models to assess relationship between NP-PCOCQ subscales and outcome measures.

2.8 ∣. Validity and reliability

The NP-PCOCQ has been widely used by researchers to study NP work environment and the tool is capable of predicting NP and patient outcomes such as NP burnout, job satisfaction or quality of care (Abraham et al., 2021; Brooks Carthon et al., 2020; Poghosyan et al., 2018). The internal consistency and construct validity of the four NP-PCOCQ subscales were assessed and validated in the study. Individual-level Cronbach's α were .94, .94, .87 and .85 for PV, NP-PR, NP-AR and IPS, respectively. Both the individual-level and group-level of the internal consistency for all four subscales were acceptable (>0.8). Confirmatory factor analysis assessed the construct validity of the instrument. Standardized root mean square residual (SRMR) and Bentler comparative fit index (CFI) were used to assess the absolute model fit due to the relatively large number of observed variables (p = 29) and the large sample size (n = 1244) (Maydeu-Olivares et al., 2018). Bootstrapping method with 500 replicates were used to obtain the 95% CIs of the indices. Results indicate a reasonable fit (SRMR: 0.062 (95% CI: 0.0585–0.678); CFI: 0.904 (95% CI: 0.889–0.910)). The model fit measured by Chi-square was significant (χ2 = 1009, df = 82, p value < .01), and the significance is probably due to the large sample size of the study (Alavi et al., 2020).

3 ∣. RESULTS

3.1 ∣. Sample characteristics

Overall, 1244 NPs completed the survey yielding a 22% response rate. Our sample size of 1244 is larger than the minimally required sample size of 500 for observational studies that involve logistic regression to derive the statistics that represent the parameters in the population (Bujang et al., 2018). The participants' demographic and work characteristics are presented in Table 1. The average age of participants was about 49 years in the overall sample, and there was no difference across SOP categories. Overall, most participants were female (87%), White (80%), non-Hispanic (91%) and did not hold a doctoral degree (88%). There were significant differences among the SOP categories in race, ethnicity and educational level (p value < .05). There was a greater racial and ethnic diversity in the restricted SOP states compared with reduced and full SOP states; in restricted SOP states, 68% of the participants were White and 15% were Hispanic.

TABLE 1.

Demographic and work characteristics of study participants

Overall sample
(n = 1244)		 Full SOP states
(n = 323)		 Reduced SOP states
(n = 396)		 Restricted SOP states
(n = 525)		 p value
Age
 Mean (SD) 48.9 (12.0) 48.9 (11.8) 49.4 (12.0) 48.6 (12.1) .56
% (n) % (n) % (n) % (n)
Gender
  Female 87 (1077) 85 (272) 90 (354) 86 (451) .07
Race
  White 80 (981) 87 (278) 90 (353) 68 (350) <.001
Hispanic 9 (111) 8 (25) 3 (11) 15 (75) <.001
Educational level
  Doctoral degree 12 (149) 19 (59) 10 (40) 10 (50) <.001
Marital status
  Married 75 (922) 76 (241) 79 (313) 71 (368) .01
Practice setting
  Physician's office 46 (569) 37 (120) 61 (236) 41 (213) <.001
   Community health centre 21 (261) 22 (72) 13 (51) 26 (138)
  Hospital-based clinic 10 (118) 12 (39) 8 (33) 9 (46)
  Other 23 (285) 28 (90) 18 (70) 24 (125)
Average hours worked/week in primary position
  <20 h 5 (58) 2 (8) 5 (20) 6 (30) .03
  20–40 h 66 (826) 66 (213) 63 (250) 69 (363)
  >40 h 29 (360) 32 (102) 32 (126) 25 (132)
Experience in primary position
  ≤3 years 45 (565) 49 (157) 42 (168) 46 (240) .14
  4–9 years 26 (317) 27 (88) 27 (107) 23 (122)
  10+ years 29 (362) 24 (78) 31 (121) 31 (163)
Experience as NP
  ≤3 years 22 (272) 25 (80) 22 (87) 20 (105) .61
  4–9 years 33 (414) 32 (104) 33 (132) 34 (178)
  10+ years 45 (558) 43 (139) 45 (177) 46 (242)
# NPs working in organization
  1 NP 17 (213) 13 (42) 23 (92) 15 (79) <.001
  2–6 NPs 63 (781) 66 (212) 55 (219) 67 (350)
  >6 NPs 6 (70) 7 (24) 4 (15) 6 (31)
  Unknown 14 (180) 14 (45) 18 (70) 12 (65)
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Note: The p value was calculated using the χ2 test with the exception of age. A one-way ANOVA test was used for age. Doctoral degree includes Doctor of Nursing Practice, PhD, or any other Doctorate. The number in parentheses next to each variable represents the number of missing data values for that variable.

Abbreviations: NP, nurse practitioner; SD, standard deviation; SOP, scope of practice.

In the overall sample, the majority of participants worked 20–40 h a week in their primary position and in organizations with two to six NPs. Additionally, the highest percentage of NPs reported practicing in physician offices, working less than 3 years in their primary position and having ≥10 years' experience as an NP. There were significant differences in SOP categories in terms of the practice setting, average hours worked per week in primary position and number of NPs working in their organization (p value < .05).

3.2 ∣. Organizational-level work environment and NP outcomes in states with variable SOP

We have compared the scores of NP-PCOCQ subscales among the online and mail respondent and did not find a difference. Descriptive statistics on work environment and outcome measures in each SOP category are presented in Table 2. In the overall sample, the highest mean scores were present in the IPS subscale with a mean of 3.48 on a 4-point scale (SD 0.47) while the lowest mean scores were present in the NP-AR subscale with a mean of 2.90 on a 4-point scale (SD 0.73). The same trends were present across all SOP categories with the IPS subscale having the highest mean scores and NP-AR subscales having the lowest mean scores. The one-way ANOVA tests indicate significant differences among the SOP categories in mean scores for PV, NP-AR and IPS (p value < .05) while there were no significant differences among the SOP categories in NP-PR mean score (p value = .63). NPs practicing in full SOP states reported the highest mean scores for NP-AR (mean = 2.99; SD 0.71), NP-PR (mean = 3.33; SD 0.54) and IPS (mean = 3.54; SD 0.43).

TABLE 2.

Descriptive statistics of predictor and outcomes variables

Overall sample
(n = 1244)		 Full SOP States
(n = 323)		 Reduced SOP states
(n = 396)		 Restricted SOP states
(n = 525)		 p value
Variable
 Organizational-level work
environment measuresb 		Mean
(SD)		 Mean
(SD)		 Mean
(SD)		 Mean
(SD)
  PV score 3.17 (0.66) 3.25 (0.64) 3.11 (0.66) 3.25 (0.64) .03c
  NP-AR score 2.90 (0.73) 2.99 (0.71) 2.81 (0.72) 2.91 (0.75) .003c
  NP-PR score 3.31 (0.54) 3.33 (0.54) 3.31 (0.54) 3.30 (0.54) .63c
  IPS score 3.48 (0.47) 3.54 (0.43) 3.43 (0.48) 3.47 (0.47) .004c
% (n) % (n) % (n) % (n)
Job satisfaction
   Very dissatisfied 2 (25) 1 (5) 2 (8) 2 (12) .97a
   Somewhat dissatisfied 8 (97) 7 (22) 8 (33) 8 (42)
   Somewhat satisfied 39 (478) 39 (124) 39 (150) 39 (204)
   Very satisfied 51 (627) 53 (168) 51 (196) 51 (263)
Intent to leave
   Very unlikely 46 (570) 50 (159) 46 (180) 44 (231) .65a
   Unlikely 32 (396) 30 (95) 34 (132) 33 (169)
   Likely 14 (173) 12 (40) 13 (53) 15 (80)
   Very likely 8 (93) 8 (27) 7 (26) 8 (40)
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Note: The number in parentheses next to each variable represents the number of missing data values for that variable.

Abbreviations: IPS, independent practice and support; NP, nurse practitioner; NP-AR, NP-administration relations; NP-PR, NP-physician relations; PV, professional visibility; SD, standard deviation; SOP, scope of practice.

a

The p value was calculated using a χ2 test.

b

Items reported on 4-point scale (‘1-strongly disagree’ to ‘4-strongly agree’).

c

The p value was calculated based on a one-way ANOVA test.

Ninety percent of NPs reported being satisfied with their current job (i.e. either ‘somewhat satisfied’ or ‘very satisfied’) while 22% of NPs reported an intent to leave (i.e. ‘likely’ or ‘very likely’ to leave their position in the next year). There were no significant differences among SOP categories in the distribution of job satisfaction categories (Pearson χ2 = 1.36, p value = .97) or for intent to leave (Pearson χ2 = 4.17, p value = .65). NPs in full SOP states reported the highest levels of job satisfaction (92%), and NPs in full and reduced SOP states both reported the lowest levels of intent to leave (20%).

3.3 ∣. The relationship between work environment and NP outcomes

There was no significant multi-collinearity in the explanatory variables; thus, all four NP-PCOCQ subscales measuring work environment were included in the final multivariable models. The effects of organizational-level work environment measures and SOP categories on the outcomes after controlling for covariates are presented in Table 3. In Model 1 with job satisfaction as the outcome variable, after controlling for covariates, a higher organizational-level NP-AR score was associated with higher job satisfaction (cumulative OR = 4.15; 95% CI: 2.81–6.12, p value < .001): with a one-unit increase in organizational-level NP-AR score, the odds of having a higher job satisfaction level increased by about four times. A higher organizational-level NP-PR score was also associated with higher job satisfaction (cumulative OR = 1.73; 95% CI: 1.13–2.66, p value < .05). Organizational-level PV and IPS scores were not significantly associated with job satisfaction. SOP was not significantly associated with job satisfaction.

TABLE 3.

Assessing the relationship between practice-level work environment scores and NP outcomes

Predictor Model 1: Job satisfactiona
Cumulative odds
Ratio (95% CI)		 Model 1
p value		 Model 2: Intent to leaveb
cumulative odds
Ratio (95% CI)		 Model 2
p value
PV score 1.128 (0.735–1.733) .578 0.968 (0.639–1.467) .877
NP-AR score 4.145 (2.806–6.121) <.001 0.392 (0.271–0.566) <.001
NP-PR score 1.733 (1.132–2.655) .012 0.635 (0.422–0.955) .030
IPS score 1.243 (0.728–2.122) .422 0.902 (0.540–1.507) .692
Scope of practice (Ref: Full)
 Restricted 1.111 (0.732–1.686) .617 1.064 (0.715–1.582) .758
 Reduced 1.267 (0.812–1.977) .294 1.047 (0.687–1.597) .828
Age category (Ref: ≤40 years)
 41–65 years 1.057 (0.714–1.566) .779 0.673 (0.464–0.976) .037
 >65 years 1.943 (0.989–3.818) .054 0.665 (0.359–1.233) .193
Non-White 0.698 (0.463–1.052) .085 1.997 (1.358–2.938) .001
Male 1.411 (0.873–2.279) .158 1.011 (0.649–1.573) .962
Practice setting (Ref: physician's office)
Community health centre 0.686 (0.444–1.059) .088 1.120 (0.743–1.688) .587
Hospital-based clinic 1.111 (0.637–1.937) .709 0.708 (0.415–1.209) .203
Other 1.031 (0.679–1.568) .884 0.805 (0.544–1.193) .278
Length of time in current primary position (Ref: NPs practiced ≥10 years)
 4–9 years 1.295 (0.852–1.968) .223 1.013 (0.682–1.507) .947
 10+ years 1.449 (0.903–2.325) .123 0.837 (0.535–1.310) .432
Hours/week worked over last month at primary position (Ref: NPs worked <20 h)
 20–40 h 1.213 (0.567–2.599) .615 0.537 (0.268–1.078) .080
 >40 h 0.603 (0.271–1.341) .212 0.665 (0.318–1.387) .274
Number of NPs in the organization (Ref: 1 NP)
 2–6 NPs 0.899 (0.582–1.389) .628 1.265 (0.833–1.921) .267
 >6 NPs 1.111 (0.510–2.421) .788 1.046 (0.498–2.198) .905
 Unknown 0.644 (0.366–1.132) .125 1.818 (1.062–3.111) .030
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Abbreviations: CI, confidence interval; IPS, independent practice and support; NP, nurse practitioner; NP-AR, NP-administration relations; NP-PR, NP-physician relations; PV, professional visibility.

a

n = 1161.

b

n = 1165.

In Model 2 with intent to leave as the outcome variable, after adjusting for the effects of potential covariates, a higher organizational-level NP-AR score was associated with lower odds of intent to leave current job (cumulative OR = 0.39; 95% CI: 0.27–0.57, p value < .001): with a one-unit increase in organizational-level NP-AR score, the odds of intent to leave current job decreased by about 60%. A higher organizational-level NP-PR score was also associated with lower odds of intent to leave (cumulative OR = 0.64; 95% CI: 0.42–0.96, p value < .05). Neither organizational-level PV nor IPS scores were significantly associated with intent to leave. SOP was not significantly associated with intention to leave.

Our results indicate that when both work environment and SOP were considered in a multivariable regression analysis, only work environment significantly predicted job satisfaction and turnover intention. SOP was not significantly associated with the outcome in either model, therefore, we reject the hypothesis about a possible relationship between SOP and NP workforce outcomes. Sensitivity analyses from mixed-effect linear regression models demonstrated similar results of relationship between work environment and NP outcomes.

4 ∣. DISCUSSION

This is the first large-scale study investigating the association between NP work environment and two workforce outcomes—job satisfaction and intent to leave, among primary care NPs in six geographically diverse U.S. states with variable SOP regulations. We found that most NPs reported being satisfied with their job; however, almost a quarter of NPs reported intent to leave their current position. Our findings also indicate that regardless of state-level SOP regulations, favourable work environments are associated with job satisfaction and reduce intent to leave among NPs, which are consistent with the literature about the importance of work environments and their potential influence on job satisfaction and intent to leave (Poghosyan, Liu, et al., 2017). Yet, our findings add more robust evidence produced from a large sample of NPs related to the crucial importance of NP relations with administration and physicians in influencing NP job satisfaction and intent to leave their job.

Specifically, we found that the relationship NPs have with administrators was associated with NPs' job satisfaction and intent to leave. Yet, among the domains of NP work environment, NP-administration relations domain was ranked the lowest by NPs. This is concerning as for decades, business management and organizational researchers have emphasized the role of administrative leadership in the success of individuals, teams and organizations. Leadership plays an important role in employee job satisfaction and retention (Long & Thean, 2011), and job satisfaction is a crucial factor determining employee commitment to the organization and their work productivity and outcomes (Aziri, 2011). Still, NPs report poor relationships with leadership characterized by leaders' lack of awareness about NP skills and competencies and lack of support for the NP role. Such evidence is concerning given the shortage of primary care providers and the impact of the relations NPs have with leadership on their job satisfaction and intent to leave—two critically important outcomes for workforce management. Our findings are consistent with past research showing consistently low score on the NP-AR subscale (Poghosyan, Liu, et al., 2017). More in-depth investigation of this relationship is critically important to understand factors that may explain the poor relationship between NPs and administrators and also take actions and design interventions to promote it. Favourable relationship between NPs and leaders is critically important as it not only affects the individual job satisfaction and performance, but also affect the overall team. Our findings are important as primary care across the globe increasingly relies on team-based care to meet the growing and evolving needs of patients, and NPs become increasingly important members of primary care teams. Research has shown NP relations with leadership have also affected the quality of teamwork between NPs and physicians (Poghosyan & Liu, 2016). Thus, favourable relationships between NPs and administrators are not only important for promoting NP job satisfaction and retention, but also for designing effective primary care teams.

Primary care practices increasingly rely on NPs regardless of state SOP laws and with an increased preference for interdisciplinary clinician configurations in team-based models. Strong leadership in primary care is critically important for increasing primary care capacity through retaining NPs and designing high-performing teams. Greater efforts are needed from leadership to enhance NP satisfaction and potentially better teamwork. One proposed strategy entails leaders adopting transformational leadership principles. Transformational leaders are capable of motivating their employees, supporting their work performance and helping the team and organization achieve the best outcomes (Wang et al., 2011). The transformational leadership principles, including fostering trust between NPs and leaders, enhancing clear communication, having a sense for common goals and leaders focusing on NP needs, may promote job satisfaction and retention.

Our findings also indicate that NPs working in clinics with favourable NP-physician relationships are more satisfied with their job and have less intent to leave their job. In this and previous studies, NPs reported favourable relationships with physicians despite concerns that overlapping scope of practice in primary care and lack of clarity between these clinicians about their respective roles could lead to strained relationships (Donelan et al., 2013; Poghosyan et al., 2020). The relationships between NPs and physicians grow stronger the more NPs and physicians work together. Clarity about roles and responsibilities of NPs and physicians in primary care may also lead to improvements in the relationship.

Even though SOP did not significantly influence NPs' job satisfaction and turnover intention, our results showed that NPs practicing with less restrictive SOP reported better work environment scores. Less restrictive SOP may indirectly improve NP workforce outcomes by creating favourable work environments (Poghosyan et al., 2021). Favourable SOP policies may help healthcare organizations to create supportive environments for NPs. Such policies will not only improve NP work environment and potentially NP workforce outcome but they will also improve access to care without compromising quality (Xue et al., 2018). Efforts should be focused on addressing organizational issues affecting the NP workforce to maximize their contributions to healthcare systems. Organizational-level policies can be designed to improve the work environment. Such favourable policies have the potential to increase the capacity of the healthcare system through optimal utilization and retention of the growing APN workforce. Our findings have implications for the professional development of nursing. As the APN workforce grows globally, our findings show that for the optimal development of the APN profession, healthcare organizations should create optimal work environments to retain these clinicians and also enable them to deliver high-quality care.

Our findings also have implications for research. The NAM model that guided our study was created to examine clinician burnout and professional well-being, which encompass concepts such as satisfaction and engagement with one's life and work (Chari et al., 2018; National Academies of Sciences, Engineering, & Medicine, 2019). We adapted the model to include job satisfaction and turnover intention. Although the NAM model was not originally designed to address these outcomes, our study demonstrated that the NAM model may be applicable in future studies examining the impact of policy and work environment on these outcomes. We indeed found relationship between NP work environment and NP outcomes guided by the NAM model.

Future studies can examine how APN workforce outcomes affect quality of care and patient outcomes in primary care. As the APN workforce is growing globally and APNs are ideally positioned to help meet the demand for primary care services, international research focusing on APN workforce and their environments and outcomes are critically important. Identifying country-specific barriers in APN work environments may be of high relevance to policymakers. Due to recent policy changes and the advancement of nursing education, now is an opportune time to analyse the APN workforce from a cross-country perspective to aid in its development and expansion.

4.1 ∣. Limitations

The study has several limitations. It relied on self-reported measures, which may be susceptible to bias. Another limitation was non-response bias. Our response rate was 22%, and it is possible that NPs who completed the survey are different from those who did not. However, the demographic characteristics in our sample mirror those of a 2018 nationally representative sample of NPs in terms of age, sex, race, ethnicity and educational level (American Association of Nurse Practitioners, 2019); for example, the average age of the participants in our study and the national sample were identical (49 years). Additionally, an overwhelming majority of our samples were female (87%), white (80%) and non-Hispanic (91%) which is consistent with the national sample (92% female, 87% white and 97% non-Hispanic). Despite our response being lower, it is typical of response rate for surveys of healthcare providers and we used best practices to increase response rate (Cho et al., 2013). NP-PCOCQ only measured NP work environment, other factors might also affect NP outcomes that are not captured in this study. Although the study was conducted in six states, the findings might not be generalizable outside of these states or internationally. Lastly, our study addressed the job resources dimension of work system factors in the NAM model, but not the job demands dimension.

5 ∣. CONCLUSION

This is the first large-scale study examining the relationship between APN work environment and job outcomes in U.S. states with variable SOP regulations governing NP practice. Study findings provide timely evidence for healthcare administrators to take actions to improve NP work environment in healthcare organizations regardless of SOP regulations. Improvements in work environments, especially relationships with administrators and physicians, may improve job satisfaction and reduce intent to leave among NPs and potentially increase healthcare workforce capacity.

Supplementary Material

supinfo

CLINICAL RESOURCES.

Guidelines on Advanced Practice Nursing 2020. https://www.icn.ch/system/files/documents/2020-04/ICN_APN%20Report_EN_WEB.pdf

Healthy Work Environment. https://www.nursingworld.org/practice-policy/work-environment/

American Association of Nurse Practitioners: Policy Briefs. https://www.aanp.org/advocacy/advocacy-resource/policy-briefs

National and Regional Projections of Supply and Demand for Primary Care Practitioners: 2013–2025. https://bhw.hrsa.gov/sites/default/files/bhw/health-workforce-analysis/research/projections/primary-care-national-projections2013-2025.pdf

Funding information

This study was funded by National Institute on Minority Health and Health Disparities [R01MD011514]. SK is supported by NIH-NINR T32NR014205 training grant.

Footnotes

SUPPORTING INFORMATION

Additional supporting information may be found in the online version of the article at the publisher’s website.

CONFLICT OF INTEREST

The authors report no conflict of interest.

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