Nursing Staffing and Quality of Life in Western New York Nursing Homes.

511154 research-article2013

WJN36610.1177/0193945913511154Shin et al.Shin et al.

Research Report

Nursing Staffing and Quality of Life in Western New York Nursing Homes

Western Journal of Nursing Research 2014, Vol. 36(6) 788–805 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0193945913511154 wjn.sagepub.com

Juh Hyun Shin1, Taesung Park2, and Ik-soo Huh2

Abstract This study investigated the relationship between nurse staffing and quality of life (QOL) in Western New York State nursing homes. This was a crosssectional, correlational study. The independent variables were hours per resident day (HPRD), skill mix, and turnover rate of nursing staff. The outcomes were measured using the self-reported QOL instrument. No coefficients were statistically significant with registered nurses’ (RNs) HPRD. Certified nursing assistant (CNA) HPRD had a statistically significant positive impact on the spiritual well-being domain. There was a statistically negative relationship between the amount of licensed practical nurse (LPN) HPRD and food enjoyment; and the ratio of more RNs to fewer LPNs and CNAs had a statistically significant negative influence on the meaningfulactivity, food-enjoyment, and security domains. The turnover of RNs had a statistically negative relationship with the sum of each domain. None of the coefficients was statistically significant with LPN turnover. Keywords nursing home, location of care, statistical analysis, methods, nursing practice, nurses as subjects

1Ewha 2Seoul

Womans University, Seoul, South Korea National University, Korea

Corresponding Author: Juh Hyun Shin, Assistant Professor, Division of Nursing, College of Health Sciences, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750, Korea. Email: [email protected]

Downloaded from wjn.sagepub.com at QUEENS UNIV LIBRARIES on March 8, 2015

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Nursing home (NH) care is a critical part of the long-term-care system in the United States, although many alternative facilities such as assisted living are emerging (Kaye, Harrington, & LaPlante, 2010). In 2004, residents in the 16,100 NHs in the United States were estimated at about 1,317,300 (Centers for Medicare and Medicaid Services [CMS], 2004). Rapidly increasing numbers of elders in the long-term-care population are expected, and more emphasis is posed on the quality of life (QOL) beyond medical-oriented measurements of quality of care (QOC; Zimmerman, Sloane, & Fletcher, 2008). QOL is defined as the ability of an individual to participate in normal activities, enjoy life free from disease or pain, pursue well-being, and be capable of performing activities of daily living (Lechich, 2011). However, many factors determine an individual’s QOL: interactions between people, regulations, the community, facility staffing, and each resident’s characteristics (Zimmerman et al., 2008). Unlike in other acute health care settings, NH residents have long-lasting and continuous relationships with nursing staff, and staffing is an important factor in determining QOL for residents (Nakrem, Vinsnes, Harkless, Paulsen, & Seim, 2009). Several systematically reviewed articles reported that increased nurse staffing was related to improved resident outcomes (Bostick, Rantz, Flesner, & Riggs, 2006; Castle, 2008; Spilsbury, Hewitt, Stirk, & Bowman, 2011). The reports from the CMS (2001) revealed that NHs that are below the standard level of staffing are more likely to have deteriorating resident outcomes. High staff turnover, staff shortages, and the way problems of NH staff and residents are addressed are major concerns in trying to manage the complex needs of the NH population (Krichbaum, Pearson, Savik, & Mueller, 2005; Winzelberg, 2003). Currently, there are two major instruments to measure QOL for NH residents. First is the self-reported QOL, which was originally developed by Kane et al. (2003) under contract with CMS to measure different aspects of QOL. CMS contracted with the University of Minnesota from 1998 to 2003 and conducted a pilot study to test 11 domains in the tentative minimum data set (MDS) 3.0’s QOL section in 100 NHs in six states (L. Anderson, Connolly, Pratt, & Shapiro, 2003). Fifty-four items were used to create the 11 QOL scales (L. Anderson et al., 2003). From a review of the literature, opinions of professionals, group discussions, and stakeholders’ discussions, the self-reported QOL instrument was developed (Kane et al., 2003). Interviews allowed researchers to hear the responses of residents directly rather than filtered through staff or family members (L. Anderson et al., 2003). MDS 3.0 stresses the psychological and social aspects of QOL (CMS, 2007), and the subset of the self-reported QOL was included as one section of MDS 3.0 (Degenholtz, Kane, Kane, Bershadsky, & Kling, 2006). CMS development team members, an information-technology coordinator, a social worker, a registered nurse


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(RN), and a physical therapist built the MDS 3.0 and received feedback through teleconferences from key stakeholders (L. Anderson et al., 2003). The second instrument is the QOL deficiencies in the Online Survey Certification and Reporting (OSCAR) data set. OSCAR includes NH characteristics and residents’ deficiencies including QOL collected during the three most current state surveys and additional complaint examinations (Harrington, Carrillo, Dowdell, Tang, & Blank, 2011). OSCAR is completed by NH administrators and collected by state survey agencies that conduct on-site evaluations at least once every 9 to 15 months as part of Medicare and Medicaid qualification requirements (Castle & Anderson, 2011; Harrington et al., 2011). After collecting data, state survey agencies enter survey information into the OSCAR database, updating it when necessary (CMS, 2006). QOL deficiencies recorded in OSCAR include residents’ dignity, freedom to decide, and the provision of social services and activities (Harrington et al., 2011). Few empirical studies have examined the relationship between nurse staffing and QOL in NHs. Very recently, researchers studied related factors to QOL; however, the majority of previous research focused on the quality measurement for NH care limited to clinically oriented effects, without considering residents’ QOL (Grabowski, 2010; Nakrem, Vinsnes, & Seim, 2011). Residents’ QOL deficiencies recorded in OSCAR were statistically significantly related to RNs’ (Johnson-Pawlson & Infeld, 1996) and certified nursing assistants’ (CNAs) hours per resident day (HPRD; Harrington, Zimmerman, Karon, Robinson, & Beutel, 2000). The QOL measured by Kane’s short QOL instrument was statistically significantly related to the commitment of CNAs (Bishop et al., 2008). However, most studies reported no statistically significant relationship between RN HPRD (Moseley & Jones, 2003; Temkin-Greener, Zheng, Cai, Zhao, & Mukamel, 2010), licensed practical nurse (LPN) HPRD (Temkin-Greener et al., 2010), CNA HPRD (Temkin-Greener et al., 2010), total nursing staff (Johnson-Pawlson & Infeld, 1996), and QOL deficiencies. Each nursing (RN, LPN, CNA) staff level did not have a statistically significant relationship with the Short QOL instrument developed by Kane (Degenholtz et al., 2006). The relationships between nursing-staff HPRD, nurse-staffing skill mix, turnover of nursing staff, and the answers given to QOL questions by 231 residents in Iowa NHs were investigated using the short QOL instrument (Shin, 2013). Although most staffing variables were not statistically associated with residents’ QOL, a few variables were significantly associated (Shin, 2013). Thus, it is necessary to examine the association between nurse staffing and QOL to confirm the relationships.


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Conceptual Framework Donabedian’s framework was selected. The structure includes all of the attributes of the settings of care and refers to the institution and capacity of the facility to offer QOC and QOL (Cameron, DiFazio, & Regan, 1997). Process refers to the tasks involved in giving and receiving care as an approach to outcomes that indicate the effect of care (Cameron et al., 1997). From the viewpoint of QOC in NHs, process is a direct assessment of care delivery, the plan of care, and interventions. Process was not examined in this study because of lack of data and measurement difficulties; process data are currently not available in a large database. Outcome is defined as a change in health status such as physical, psychological, or social functioning in response to provided care. Structure and process may impact outcomes directly or indirectly, and the importance of each component of structure and process depends on complex factors (Campbell, Roland, & Buetow, 2000). Outcomes in NHs represent the changes in health and conditions ascribed to the care given or not given, symptom relief, and knowledge and behavioral changes in health (Schirm, Albanese, & Garland, 1999). In this study, QOL variables were measured as outcome variables. The purpose of this study was to investigate the relationship between nurse staffing and QOL in Western New York NHs. The following are the hypotheses: Hypothesis 1: Higher nurse-staffing HPRD is associated with higher QOL scores. Hypothesis 2: Higher portions of RNs (compared with LPNs and CNAs) are associated with higher QOL scores. Hypothesis 3: Higher turnover rate of nursing staff is associated with lower QOL scores.

Method Design of the Study The design was a cross-sectional, correlational study.

Sample/Setting We used convenience snowball sampling. Principal Investigaro of this study contacted administrators of four NHs in Western New York State with the help of the State University of New York School nursing faculty; additional


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NHs were recruited by the contacted NHs. A total of 142 residents from 8 selected NHs within 100 miles of Buffalo (certified for Medicare and Medicaid) were included in the sample. In this study, cognitively intact residents and slightly demented residents were invited to participate in interviews to express their views of QOL, provided their Mini Mental State Examination score was higher than 13. Long-term and recently admitted residents were included. Exclusion criteria were comatose residents, terminally ill residents, residents with severe cognitive and functional impairments, residents younger than 65 years, and residents admitted for rehabilitation purposes. After completing interviews, demographic information including age, gender, admission date, education, socioeconomic status (insurance type), and Resource Utilization Groups (RUGs) were collected from subjects’ charts. Because the only available electronic source on staffing was the OSCAR (Kane et al., 2003), the federal OSCAR data set for the year 2010 was purchased to measure staffing independent variables through the Cowles Research Group (Shin, 2011). Using 44 RUGs classifications, residents’ acuity was controlled statistically, because physically and cognitively impaired residents were presumed to have negative effects on their general health, finally impacting their QOL. To control extraneous variables, RUGs classifications were changed to numerical values. The range of the case-mix index was from 0 to 1.86. Larger numbers indicated weaker residents.

Instruments Staff measures. Independent variables were HPRD, skill-mix HPRD, and turnover rates of nursing staff. Each nurse-staffing HPRD and skill-mix HPRD were obtained from OSCAR and the primary data collection for turnover (crude turnover rates) was obtained from the administrative staff at each NH using the Nursing Personnel Data Collection Tool developed by Bostick, and the crude turnover rate was calculated (Duxbury & Armstrong, 1982). OSCAR is the only available electronic source on NH staffing through Straker (1999). Thus, the federal OSCAR data set for the year 2009 was purchased to measure staffing independent variables through the Cowles Research Group. The definition of HPRD by CMS (CMS, 2013) was applied; HPRD refers to average hours worked by licensed nurses or nursing assistants divided by total number of residents. The operational definition of the skill mix was the ratio of RNs to LPNs/licensed vocational nurses (LVNs)/ CNAs and was used as a tool to measure skill mix. In addition, the demographic information about nursing-staffing variables was collected directly from the administrative staff in each NH.


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Self-reported QOL instrument. The self-reported QOL instrument is a welldeveloped, easy-to-administer tool in the public domain to measure QOL of NH residents in the United States. This instrument consists of 54 questions in the 11 QOL domains covering comfort, functional competency, privacy, meaningful activity, autonomy, food enjoyment, spiritual well-being, security, individuality, dignity, relationships, and security (R. Anderson, Issel, & McDaniel, 2003). A higher score on the QOL instrument represented more positive QOL. The range of each domain was different, and individual criterion measures for separate domain scale and total score of each domain were analyzed in this study. Residents were asked to respond to the following items in the comfort domain: (a) whether they feel too cold, (b) whether they have physical pain, (c) whether they stay so long in the same position that it hurts, (d) whether they are interrupted by noise in their room, (e) whether they are interrupted by noise elsewhere in NHs, and (f) whether they have a good night’s sleep. The average score in the comfort domain was quite high: 16.25 (SD = 5.53); the score ranged between 6 and 24. In the functional-competence domain, residents responded to the following items: (a) whether they can easily get around by themselves, (b) whether they can easily reach things that they need, (c) whether they can get to the bathroom quickly, (d) whether they can reach toilet articles without difficulty, and (e) whether they can take care of their own things and their room as much as they want. The average score in functional competence was 15.48 (SD = 4.54); the score range was between 5 and 20. In the privacy domain, items referred to residents’ ability to (a) be alone, (b) make a phone call, (c) have privacy with visitors, (d) have privacy with other residents, or (e) have privacy when the staff knocks and waits for their reply before entering their room. The average score in the privacy domain was quite high: 13.77 (SD = 4.8); the score ranged between 5 and 20. In the dignity domain, residents were asked whether the NH staff (a) treats them politely, (b) treats them with respect, (c) handles them gently, (d) respects their modesty, and (e) takes time to listen to them when they have something to say. The average score in the dignity domain was 16.54 (SD = 4.74); the score range was between 5 and 20. In the meaningful-activity domain, residents were asked whether they (a) get outdoors as much as they want, (b) have enjoyable things to do on weekends, (c) have enjoyable activities at NHs, and (d) help others. The average score in the meaningful-activities domain was 16.10 (SD = 4.16); scores ranged between 6 and 24. In the relationship domain, residents answered five questions, including whether (a) it is easy to make friends at NHs, (b) they consider any resident to be their close friend, (c) staff stop by just to have a friendly conversation with them, (d) they consider any


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staff members to be their friend, and (e) NHs make it easy for family and friends to visit. In the autonomy domain, residents were asked whether they (a) go to bed at the time they want, (b) can get up in the morning when they want to, (c) can decide what clothes to wear, and (d) can change when they want to change something. The average score in the autonomy domain was low: 11.12; scores ranged between 4 and 16. In the enjoyment domain, residents were asked whether (a) they like food, (b) enjoy mealtimes, and (c) can get their favorite foods at the NH. The average score in the food-enjoyment domain was quite moderate: 8.98 (SD = 3.95); scores ranged between 3 and 12. The spiritual well-being domain queried the following items: whether (a) residents participated in religious activities, (b) those activities are meaningful, (c) they feel that life as a whole has meaning, and (d) they feel at peace. The average score in the spiritual well-being domain was 10.88 (SD = 3.24); score range was between 4 and 16. In the security domain, residents were asked whether (a) their belongings are safe, (b) their clothes get lost or damaged in the laundry, (c) they feel convinced that they can get help when needed, (d) they can get a nurse or doctor quickly, and (e) they are afraid because of the way the NH staff treats the residents or how other residents are treated. The average score in the security domain was 16.73 (SD = 3.98); score range was between 5 and 20. In the individuality domain scale, residents were asked whether (a) staff knows about their interests; (b) staff knows about their experiences, and what residents did in their pre-NH lives; (c) staff know the resident as a person; (d) other residents know the resident as a person; (e) staff take the preferences of residents sincerely; and (f) the desires and interests of residents are respected at NHs. The average score in the individuality domain was quite high: 17.88 (SD = 5.85); score range was between 6 and 24. Residents answered five questions in the relationship domain, including whether (a) it is easy to make friends at NHs, (b) they consider any resident to be their close friend, (c) staff stop by just to have a friendly conversation with residents, (d) they consider any staff members to be their friend, and (e) NHs make it easy for family and friends to visit. The average score in the relationship domain was high: 14.23 (SD = 4.31). Residents were asked whether (a) their belongings are safe, (b) their clothes get lost or damaged in the laundry, (c) they feel convinced that they can get help when needed, (d) they can get a nurse or doctor quickly, and (e) they are afraid because of the way the NH staff treats the residents or how other residents are treated. The average score in the security domain was 16.73 (SD = 3.98). The psychometric characteristics of the self-reported QOL instrument were reported to be good; internal consistency ranged from alpha = .52 to .76


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(Kane, 2003), indicating good validity between each domain and summary measures (CMS, 2007). Furthermore, I tested psychometric characteristics of the self-reported QOL instrument. The interrater reliability was reported to be good, between .73 and 1.0. Criterion validity was measured between the relationship scale in the QOL of the MDS 3.0 and the relationship indicator of Nursing Outcomes Classifications and was reported to range from .34 to .58 (Shin, 2011). The alphas for each domain in the current study are as follows: dignity (α = .65), comfort (α = .77), privacy (α = .67), meaningful activity (α = .85), relationships (α = .77), spiritual well-being (α = .80), autonomy (α = .62), individuality (α = .87), food enjoyment (α = .76), security (α = .88), and functional competence (α = .65). RUGs. CMS started its Nursing Home Casemix and Quality Demonstration project in various states using MDS and other measures (Wunderlich & Kohler, 2001). Based on these data, RUGs-III advanced (Wunderlich & Kohler, 2001) MDS categorizes residents into 44 different RUGs for the Medicare prospective payment system (Wunderlich & Kohler, 2001). Reliability and validity were tested (Mueller, 2000). The 44 RUGs are classified based on seven major categories: rehabilitation, extensive services, special care, clinically complex, cognitive impairment, behavioral problem, and physical function (Mueller). NHs with residents who belong to higher RUGs are paid more than those with lower RUGs (Wunderlich & Kohler, 2001). In this study, RUGs were used to control residents’ different functional status. The RUGs classification was converted to numbers to be used as control variables based on the casemix set B02, which was developed for research by CMS (2007). These factors were considered to investigate the relationship between staffing variables and QOL. The obtained RUGs sample data (N = 142) had 23 categories, and each group functioned as one control variable.

Data Collection Before data collection began, we contacted administrators of four NHs in the Western New York State area with the help of the State University of New York School nursing faculty. Convenience snowball sampling was used to recruit additional NHs. We visited selected NHs to introduce this study to administrators and obtained the list of residents who met the inclusion criteria to be interviewed by a research assistant (RA). The administrator or director of nursing (DON) was asked to identify the availability of residents to answer the questionnaire. The trained RA asked participants questions in person.


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QOL was based on each person’s own values, beliefs, and faith. QOL is quite subjective and complex to assess, and the best way to measure is to get answers from residents directly (Duxbury & Armstrong, 1982). Although most NH residents experience different levels of cognitive impairment, it was reported that some residents, even those with mild cognitive impairment, could take part in interviews (Crespo, Bernaldo de Quirós, Gómez, & Hornillos, 2012; Kane et al., 2003). The trained nurse RA obtained residents’ consent and collected QOL data directly from the residents. Originally, 164 residents were accessed, 22 refused, and a total of 142 residents completed the interview. The average time required to complete the interview per resident was 26.48 min (SD = 20.00 min).

Data Analysis The mixed-effects model was used to analyze the data. Because NH effect may exist, heterogeneity in subjects between NHs needed to be handled appropriately. Thus, NH effect was treated as a random effect. Power analysis using a simple mixed-effects model with only one fixed effect of interest was performed; I found that the 142 sample size in the study was large enough to provide about 80% power for 7 of the 10 fixed effects (variables) of interest. We examined the association between the 5 variables of interest on staffing and 11 dependent variables related with QOL; we summed and examine QOL scores using the mixed-effects model. Age, gender, length of stay, RUGs, race, education, and socioeconomic status were used as controlling variables. To conduct analysis, the MIXED procedure of SAS 9.3 was used. We found variables with coefficients that satisfy p value below .05 and .1.

Ethical Consideration We obtained approval from the Institutional Review Board of the State University of New York at Buffalo.

Results Characteristics of Facilities, Nurse Staffing, and Participants The average number of beds in participating organizations was 152 (SD = 54.1), ranging from 80 to 250. More than half (5 of 8) were for-profit facilities. About 14.08% of participants were covered by Medicare; about 55.64% of participants were covered by Medicaid; 10.56% were paid by private pay.


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Shin et al. Table 1. Nurse-Staffing Characteristics. Characteristics RN (number) LPN (number) CNA (number) DON (number) RN HPRD (minutes) LPN HPRD (minutes) CNA HPRD (minutes) LPN age (years) CNA age (years) RN experience (years) LPN experience (years) CNA experience (years)

M

SD

Minimum

Maximum

10.16 29.89 65.30 1.07 39.00 52.40 133.00 39.73 32.9 8.19 8.65 5.09

6.44 10.69 25.31 0.03 10.34 5.89 13.49 3.31 4.54 1.72 2.90 0.86

2 12 20 1 26 48 116 36 27 6.58 6.95 4.27

13 34 89 1.14 54 62 150 43 37 10 12 6

Note. RN = registered nurse; LPN = licensed practical nurse; CNA = certified nursing assistant; DON = director of nursing; HPRD = hours per resident day.

The characteristics of nurse staffing are summarized in Table 1. LPNs outnumbered RNs three to one. RNs and LPNs had about the same number of years of service. The average number of RNs, LPNs, CNAs, and DONs was 10.16 (SD = 6.44), 29.89 (SD = 10.69), 65.3 (SD = 25.31), and 1.07 (SD = 0.03) per NH, respectively. The average HPRD of RNs, LPNs, and CNAs was 39 (SD = 10.34), 52.4 (SD = 5.89), and 133 (SD = 13.49) min, respectively. The average age of RNs was 45.51 years (SD = 3.31), with 8.19 years of professional experience. The average age of LPNs was 39.73 years, and the average professional experience earned was 8.65 years. The average age of CNAs was 32.9 years, with an average professional experience of 5.09 years. Participants’ average age was 80.03 years (SD = 10.6). The average length of stay in the current NH was 2 years 2 months (SD = 10.8 months). Most resident participants were women (77.5%), White (82.4%), and widowed (47.91%), and had attained a high school diploma (61.9%).

Nursing-Staff HPRD The mean and standard deviation scores for each domain are presented in Table 2. A higher score represents a more positive QOL. The relationship between nursing-staff HPRD of RNs, LPNs/LVNs, and CNAs and QOL were explored and are summarized in Table 3.


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Table 2. Mean and Standard Deviation for the Proposed Minimum Data Set 3.0 Quality of Life Measures for the Sample of 142 Residents in Western New York. Domain Comfort Functional competence Privacy Dignity Meaningful activity Relationship Autonomy Enjoyment Spiritual well-being Security Individuality Summary

Number of Items

Score Range

M

6 5

6-24 5-20

16.25 15.48

5.53 4.54

5 5 5 5 4 3 4 5 6

5-20 5-20 6-24 5-20 4-16 3-12 4-16 5-20 6-24 NA

13.77 16.54 16.10 14.23 11.12 8.98 10.88 16.73 17.88 32.15

4.80 4.74 4.16 4.31 3.59 3.95 3.24 3.98 5.85 10.91

SD

Note. A higher score represents more positive QOL. The item of sum was not summed to create a scale, but used as individual criterion measures for the separate domain sales.

RN HPRD. None of the 11 coefficients was statistically significant for RN HPRD. LPN and LVN HPRD. Contrary to the expectation, there was a statistically significant negative relationship between the amount of LPN HPRD and food enjoyment (β = −4.9, p < .05). In other words, residents were less satisfied with food in NHs when more LPN hours were provided. Certified nurse aids HPRD. CNA HPRD had a statistically significant positive impact on one of the 11 staffing coefficients: the spiritual well-being (β = 5.013, p < .05) domain. In other words, as more CNA hours were provided, residents were more satisfied with their religious lives.

Skill Mix Skill mix was examined to see whether it was a predictor of QOL for NH residents. Contrary to expectations, the ratio of more RNs to fewer LPNs and CNAs had a statistically significant negative influence on meaningful-activity (β = −0.066, p < .005), food-enjoyment (β = −0.064, p < .05), and security (β = −0.145, p < .05) domains. In other words, more LPN and CNA staffing, compared with RN staff, was related to better scores in the meaningful-activity, enjoyment, and security domains.



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PRI

0.4453

0.8772

−2.9885 −3.1551 −5.457 −3.7026

FC

0.00151 0.0012 −0.0093 0.02557 −0.0081 −0.0595 0.01244 −0.0209 0.01203 0.02297 −0.0004 −0.0891

−2.2435

0.6593 −0.5991

CMF

−1.04

−1.71 −1.38

MA

1.516

−7.168 −0.387

REL

−0.019* −0.007* −0.014 −0.102 −0.016 −0.045 −0.035 0.007 −0.016 −0.150 −0.066* −0.095

5.295

−2.23 −1.445

DIG

−0.944

−2.54 −4.90*

ENJ

−0.007 −0.004 −0.045 0.0015 −0.051 0.0004 0.014 −0.064*

2.52

−3.94 4.99

AUT

−0.009 −0.039 −0.049* −0.027

5.013*

−4.107 5.469

SWB

−0.014** −0.044 −0.003 −0.145*

0.541

−2.99 −4.75

SEC

−0.019 −0.112 −0.032 −0.121

4.063

−4.095 1.793

IND

−0.0044* 0.0012 −0.0028 −0.062

1.304

−5.23 −3.57

Sum

Ratio of RNs to LPNs/LVNs + CNA (RN: LPN + CNA); Calculation formula for crude turnover rate with the Application of Nursing Personnel Collection Tool developed by Bostick: Crude turnover rate for RNs =1 / 2 (total number of RN employed as of January 2010 + total number of RN employed as of October 2010) × 100; Crude turnover rate for LPNs =1 / 2 (total number of LPN employed as of January 2010 + total number of LPN employed as of October 2010) × 100; Crude turnover rate for LPNs =1 / 2 (total number of CNA employed as of January 2010 + total number of CNA employed as of October 2010) × 100. CMF = Comfort; FC = Functional Competence; PRI = Privacy; DIG = Dignity; MA = Meaningful Activity; REL = Relationship; AUT = Autonomy; ENJ = Enjoyment; SWB = Spiritual Well-being; SEC = Security; IND = Individuality; SUM = Summary; HPRD = hours per resident day; RN = registered nurse; LPN = licensed practical nurse; CNA = certified nursing assistant; LVN = licensed vocational nurse. *p < .05 **p < .01.

Note. Staffing hours per resident day calculations—RN HPRD:

Computed RN hours per day = RN hours per resident day; LPN HPRD: Bed size Computed CNA hours per day ComputedLPNhours per day = CNA hours per resident day; Skill mix: = LPN hours per resident day; CNA HPRD: Bed size Bed size

HPRD RN HPRD LPN HPRD CNA HPRD Turnover RN LPN CNA Skill Mix

Staffing

Table 3. Influence of Nursing Staff on Residents’ Quality of Life (t-Values).

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Turnover As expected, there was a statistically significant negative relationship between the turnover of RNs and the dignity (β = −0.019, p < .05), meaningful-activity (β = −0.007, p < .05), and security (β = −0.014, p < .01) domains. Interestingly, the turnover of RNs had a statistically significant negative relationship with the sum of each domain (β = −0.0044, p < .05). None of the coefficients were statistically significant with LPN turnover. For CNA turnover, only one domain, spiritual well-being (β = −0.049, p < .05), had a statistically negative relationship with the turnover of CNAs.

Discussion In this study, few nurse-staffing variables were statistically significant in each of the QOL domains. Results were not consistent across staff types. Some studies reported no relationship between nurse staffing and QOL (Degenholtz et al., 2006; Johnson-Pawlson & Infeld, 1996; Moseley & Jones, 2003; Temkin-Greener et al., 2010). The lower turnover rate of RNs contributed to the dignity, meaningful-activity, and security domains and summed QOL scores and lower turnover rate of CNAs contributed to the spiritual well-being domain. Although it was not exactly consistent with previous research, Bishop et al. (2008) reported that QOL measured by the short QOL index from the self-reported QOL instrument was higher in units where the proportion of CNAs with higher intention to stay in their organization was higher. The more committed nursing staff are the more likely to have encouraging interaction with residents (Bishop et al., 2008). The major differences between this study and previous studies were that this study reported the effects of nurse staffing on each domain of QOL, whereas previous studies reported the effects of staffing on overall QOL across 11 domains. The highest beta coefficient value for contribution to explaining the QOL was CNA HPRD on spiritual well-being (β = 5.013), followed by the LPN HPRD on food enjoyment (β = −4.9), when the variance by all other variables in the model are controlled. It was reported in this study that residents with more HPRD of CNAs are more satisfied with their participation in religious services at each NH. Most participating NHs had religious services, but some respondents wished to have individualized religious services. For example, NHs usually provided one church service and some residents went out for church because NHs did not provide services for their church denomination. In some cases, residents mentioned that they did not know whether there were religious services or whether their physical conditions, such as arthritis pain or mobility limitations, hindered their participation in religious


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services. Thus, more NH staff hours per day may make residents satisfied with their spiritual well-being because staff are aware of specific needs of religions and can help them participate in religious activities. The next highest beta coefficient was LPN HPRD on food enjoyment, which meant that more provided LPN hours were related to less food enjoyment in this study. Consistent with previous research (Dyck, 2007; Shin, 2013), most residents answered that they do not have specific favorite foods; more than half of the interviewed residents did not like waiting for meals. It seems that LPNs cannot resolve the issues raised during mealtimes. This study supported the concept that stable RN staffing was related to dignity, meaningful activity, security, and summed QOL score, which is a complex result when compared with previous research. In the previous study (Shin, 2013), more RNs’ HPRDs were associated with better comfort; the unique contribution of more RNs was supported in the functional competence of residents. However, this study did not support the relationship between RN HPRD and any QOL domains. In other words, results implied that the more residents have stable, tenured RNs staffing, the more content they were with dignity, meaningful activity, and security. Some previous research supported the contribution of RN HPRD and QOL; Residents’ QOL deficiencies recorded in OSCAR were statistically significantly related to RNs HPRD (Johnson-Pawlson & Infeld, 1996) and CNAs HPRD (Harrington et al., 2000). Harrington et al. (2000) and Bishop et al. (2008) reported that CNA HPRD and level of commitment to the organization were statistically related to QOL deficiencies. In this study, CNA hours were related to spiritual well-being of residents; more CNA hours and less CNA turnover were more related to higher satisfaction of residents about their religious lives. This finding suggests that CNAs participate more in religious activities or conversation with residents about religion. However, previous research (Shin, 2013) reported that less CNA turnover was important for the security and individuality domains. Previous research (Shin, 2013) that examined QOL of residents as outcomes of interest reported that nursing-staff turnover was positively correlated with some domains of QOL for some residents, for example, showing a higher score in the enjoyment domain with increased RN turnover. However, increased turnover did not contribute to any QOL domains in this study. No coefficients were statistically significant with LPN turnover in this study, whereas higher scores in the individuality, privacy, and relationship domains were related to increased turnover of LPNs, inferring that newly hired LPNs are more willing to establish rapport and learn about the residents in previous research (Shin, 2013). Findings from this study cannot be generalized to draw conclusions about the effect of nurse staffing on


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residents’ QOL and more research throughout the United States is necessary to confirm findings. This study furthers knowledge of the level of QOL in NHs and an understanding of how staffing relates to residents’ QOL. More research on staffing and QOL is needed to draw inferences for national policy (Kramer & Fish, 2001). To establish and improve QOL in NHs by establishing legal optimized ratios of nurse staffing and nursing-care hours, it is important to explore and define RNs’ contribution to QOL in NHs. RNs’ unique contribution to resident outcomes in comparison with alternative nurse staffing requires further research to see which staffing mix maximizes desirable outcomes for residents. However, several factors may not accurately reveal the effects of nurse staffing on residents’ QOL outcomes. The advantages of nurse staffing may be identified, bounded by some threshold (Schnelle et al., 2004), and the nurse staffing in this study may fail to reach this threshold (Xu, Kane & Shamliyan, 2013). The impact of nurse staff on resident QOL outcomes may be mediated by other factors, including geriatric education, staffing turnover, job satisfaction, experience of staff, and supervision (Xu, 2013). The threat to internal validity and generalizability should be considered. To recruit participants, I asked the administrator or DON of each NH to identify the tentative respondents to be interviewed. Consequently, this potential selection bias may have resulted in underrepresentation of some NH residents. I could not contact the residents of each NH if the administrative staff did not allow me to do so, and further research is required with a larger sample size. Furthermore, the development of instruments to measure QOL for NH residents is required. Neither QOL deficiencies in OSCAR nor the selfreported QOL instrument can identify multidimensional aspects of QOL of residents comprehensively (Degenholtz et al., 2006). The OSCAR does not include all residents’ QOL and the surveyors, not residents, judge QOL deficiencies (Degenholtz et al., 2006). Section F (preferences for customary routine and activities) of the MDS 3.0 did not include all the QOL items developed by Kane et al. (2003). Thus, more research is required to explore the relationship between nursing turnover and residents’ QOL. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been supported by the Sigma Theta Tau International.


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