WORKLOAD of HOME HEALTH CARE NURSES in JAPAN By

WORKLOAD OF HOME HEALTH CARE NURSES IN JAPAN

KEIKO OGAWA

Submitted in partial fulfillment of the requirements

For the degree of Doctor of Philosophy

Dissertation Adviser: Dr. Elizabeth Madigan

Frances Payne Bolton School of Nursing

CASE WESTERN RESERVE UNIVERSITY

May, 2008

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the theses/dissertation of

KEIKO OGAWA

Candidate for the PhD degree*

(signed) Elizabeth Madigan (chair of the committee)

Diana Morris

Susan Tullai-McGuiness

Robert Binstock

(date) March 6, 2008

*We also certify that written approval has been obtained for any proprietary material contained therein.

Table of Contents

Page

Table of Content------i

List of Tables------v

List of Figures------vii

Acknowledgements------viii

Abstract------ix

CHAPTER I: Introduction ------1

Introduction------1

Problem and Significance Statements ------2

Conceptual Framework------8

Concepts in the Present Study------9

Definition of Terms------14

Research Questions ------14

Significance to Nursing Science and Practice------15

Nursing Science ------15

Nursing Practice------16

CHAPTER II: Review of the Literature ------18

Job satisfaction ------18

Job satisfaction ------30

Relationship between job satisfaction and nurse characteristics------32

Productivity------33

Relationship between productivity and nurse characteristics ------34 ii

Relationship between productivity and job satisfaction------35

Productivity ------35

Time spent in home-visit nursing care ------41

Gaps in the literature------48

CHAPTER III: Methodology------52

Design ------52

Settings and Samples ------57

Sample Size and Power Analysis ------58

Data Collection Procedure ------59

Measurements ------60

NWI-R------60

Reliability and Validity------63

Statistical analysis ------65

Research Questions ------65

Protection of Human Subjects------67

Chapter IV: Results ------69

Recruitment------69

Sample Description ------70

Job Satisfaction------74

Reliability and Validity ------77

The NWI-R ------77

Analyses to Answer Research Questions ------77

Testing Assumption of Multiple Regression ------77 iii

Research Question 1 ------78

Research Question 2 ------82

Research Question 3 ------86

Research Question 4 ------88

Research Question 5 ------89

Summary ------92

Chapter V: Discussion------94

Discussion of Results------94

The Relationships between Nurse Characteristics and Job Satisfaction ------94

Job Satisfaction------95

The Productivity of Japanese Visiting Nurses------100

The Relationships between Nurse Characteristics and Productivity------103

The Relationships between Productivity and Job Satisfaction ------104

The Relationships between Nurse Characteristics and Productivity, and Job

Satisfaction------104

Implications for policy, theory and administration ------105

Implication for policy------105

Implication for theory ------107

Implication for administration------108

Limitations------108

Suggestions for future research ------109

Summary ------110

APPENDIX A: Nurse Workload Form ------113 iv

APPENDIX B: Nurse Questionnaire ------120

APPENDIX C: Study Variables ------122

APPENDIX D: Cover Letter ------125

APPENDIX E: A letter of cooperation------126

APPENDIX F: Cover Letter------127

APPENDIX G: Informed Consent Document------128

BIBLIOGRAPHY ------130

List of Tables

Table 1: A summary of the relevant research:

Job satisfaction and nurse characteristics------20

Table 2: A summary of the relevant research:

Productivity and nurse characteristics ------34

Table 3: Example of calculating productivity by Power’s (1987) formulas------40

Table 4: A summary of the relevant research:

Time spent in home-visit nursing care------42

Table 5: A summary of the relevant research: Research design ------53

Table6: Sample Characteristics: Age and Years of Experience------71

Table7: Age Distribution------72

Table8: Sample Characteristics: Gender, Employment status, and Education------73

Table9: Job Satisfaction (The NWI-R and the overall job satisfaction) ------76

Table10: Correlation of nurse characteristics with job satisfaction (the NWI-R)------80

Table11: Correlation of nurse characteristics with job satisfaction (the overall job

satisfaction) ------80

Table12: Regression Analysis for Variables predicting job satisfaction (the NWI-R)---81

Table13:Regression Analysis for Variables predicting job satisfaction (the overall job

satisfaction)------81

Table14: Workload (total hours, visits number, and working days)------83

Table15: Workload (Type of visits)------83

Table16: Workload (care time minutes)------84

Table17: Productivity (Visits per day)------85 vi

Table18: Correlation of nurse characteristics with productivity------86

Table19: Regression Analysis for Variables predicting productivity------87

Table20: Correlation of nurse characteristics and productivity with job

satisfaction (the NWIR)------90

Table21: Correlation of nurse characteristics and productivity with job

satisfaction (the overall job satisfaction)------90

Table 22: Regression Analysis for Variables predicting job

satisfaction (the NWI-R)------91

Table 23: Regression Analysis for Variables predicting job

satisfaction (the overall job satisfaction)------91

Table 24: Comparisons between the NWI-R results in the present study and

the previous study------98

vii

List of Figures

Figure 1: Conceptual framework of the present study------13

Figure2: Histogram of the overall job satisfaction scores------75

viii

Acknowledgements

I would like to express my appreciation to many people who supported and encouraged me to finish this work. First of all, I would like to thank Dr. Elizabeth

Madigan, PhD, FAAN, RN, the chairperson of my dissertation committee. She guided me throughout my graduate study. I also would like to thank Dr. Diana Morris, PhD, FAAN,

RN, Dr. Susan Tullai-McGuiness, PhD, RN, and Dr. Robert Binstock, PhD, who gave many insights of my dissertation as my committee members.

Next, I would like to acknowledge Dr. Setsu Shimanouchi, PhD, RN, former professor of Tokyo Medical and Dental University, Dr. Michiko Fukushima, DSW, RN, professor of the Japanese Red Cross College of Nursing, and Dr. Akiko Sasaki, PhD, RN, professor of Tokyo Medical and Dental University. They recommended me to study PhD program in the U.S. I appreciate their encouragement. I also appreciate ICN Tokyo

Congress Scholarship. I was financially supported to study throughout my PhD coursework and dissertation process in the U.S.

I wish to extend my gratitude to some special people who supported my dissertation process: to Dr. Tomoko Kamei, PhD, RN, professor of St. Luke’s College of

Nursing, Dr. Naoko Tomoyasu, PhD, former associate professor of Tokyo Medical and

Dental University, Dr. Yoko Uchida, PhD, RN, associate professor of Gunma University,

Dr. Setsu Shimanouchi, PhD, RN, professor of International University of Health and

Welfare, and Dr. Mia Kobayashi, PhD, RN, assistant professor of International

University of Health and Welfare. I appreciate their thought and support for my dissertation process.

Finally, I am grateful to my family and many friends in Japan and the U.S. ix

Workload of Home Health Care Nurses in Japan

Abstract

KEIKO OGAWA

The role of home-visit nursing care is increasingly important in Japan. The

number of Visiting Nurse Stations (VNSs) is less than sufficient to provide nursing services to patients at home and there is a lack of research on the topic. The purpose of

this study was to identify productivity in home-visit nursing care in Japan and to examine relationships between nurse characteristics, productivity, and job satisfaction, guided by the Donabedian structure-process-outcome model. A descriptive correlational design was used. There were 28 VNSs and 100 home care nurses providing data and two instruments in the survey: the nurse workload form (time survey) and the nurse questionnaire (the

Nursing Work Index-Revised and a single item indicator of satisfaction using a visual analog scale). Nurses in this study were on average 40.4 years old (SD = 8.4) and had, on average, 14.8 years (SD= 7.7) of experience as a nurse. The findings indicated that nurse characteristics (age, employment status, and years of experience) and productivity did not explain a significant amount of variance in job satisfaction for either measure. There was a weak, negative correlation (r=-.19; p=.03) between productivity and job satisfaction score from the NWI-R. When there was higher productivity, there were lower scores on the NWI-R, suggesting that nurses who have more productivity had lower satisfaction. x

The results showed that productivity was 3.76 (SD = 1.05) visits/day using the

formula that included both direct and indirect care. Visiting nurses spent average 1018

(SD = 454) minutes for one week in direct care and averaged 766 (SD = 407) minutes for one week in indirect care. The proportion of direct care / indirect care was 58/42 ratio.

The percentage for the amount of indirect care time spent on each activity was as follows: travel (41.5%), documentation (20.2%), telephone (4.5%), meeting (14.4%), preparation

(8.0%), and others (11.4%). Nonvisit work was a significant portion of the time spent by visiting nurses in Japan and may explain the relationship between productivity and satisfaction. The results of the present study are important in understanding the work environment of nurses in home health care settings in Japan. 1

Chapter I

Introduction

The role of home-visit nursing care is increasingly important in Japan following the implementation of Long-Term Care Insurance (LTCI) in 2000. However, the current number of Visiting Nurse Stations (VNSs) is less than sufficient to provide nursing services to patients at home (Japanese Nursing Association, 2003), and the number of

VNSs has not increased as recommended. Although home-visit nursing care became much more important after the LTCI system started in 2000 in Japan, there is a lack of

research on home-visit nursing care in Japan.

Based on the growth in the proportion of older people, more VNSs are needed in

Japan (Japanese Nursing Association, 2003). However, there are few studies on how

nurses within VNSs actually work. Exploring the workload of visiting nurses might

prompt a discussion of ways to facilitate increasing the number of nurses and establish

more VNSs in Japan. One factor that has been identified in the U.S. as responsible for a

decrease in nursing staff was the excessive workload of home health care nurses

(Ellenecker, Neal-Boylan, & Samia, 2006). Also, studying the work done by visiting

nurses might shed light on the factors related to their job satisfaction. This research may

suggest ways to improve visiting nurses’ work environments and potentially contribute to

policy discussions on how to increase the number of visiting nurses and VNSs.

The purpose of this study was to identify productivity in home-visit nursing care

in Japan and examine relationships between nurse characteristics, productivity, and job

satisfaction. There is no published research that focuses on the productivity of home-visit nursing care in Japan. The structure-process-outcome (SPO) model by Donabedian 2

(1966) guides the present study, including concepts, research questions, and research

design. This study was the first, to our knowledge, to include relationships between productivity and job satisfaction among visiting nurses in Japan.

Problem and Significance Statements

In Japan, there is a growing need to enhance home-visit nursing care for the

following reasons. First, aging is an issue of concern in Japan because the percentage of

aging people is increasing. The world’s elderly people have been increasing at the rate of

795,000 each month (Kinsella & Vistoria, 2001). Much like the global population, Japan

has experienced an increase in the number of elderly people. According to the Japanese

Health and Welfare Statistics Association (2002), in 2000 the population aged 65 years

and older was comprised of 22,041,000 people (17%), while the total population in Japan was 126,926,000. In the 20 years between 1980 and 2000, the proportion of people aged

65 and over in Japan increased from 9.1 % to 17.4%. Also, it is estimated that the proportion will reach 22.5 % (28,614,600 of 127,176,000 people) in 2010, 27.8 %

(34,120,330 of 122,735,000 people) in 2020, and 29.6 % (34,106,304 of 115,224,000 people) in 2030 due to the decrease in birth rates and the increase in longevity. Moreover, the proportion of people aged 65 and older in Japan will be 35.7 % (33,969,264 of

95,152,000 people) in 2050 (The Japanese Health and Welfare Statistics Association,

2002 & National Institute of Population and Social Security Research, 2008). These dramatic demographic changes required restructuring of health services (Ikegami, 1997), leading to the establishment of the new law, LTCI, which promotes community services such as home-visit nursing care. The Ministry of Finance, Health and Welfare, and Home

Affairs projected the demand for VNSs for LTCI in Japan. 3

A second reason to better understand home-visit nursing care is related to the

length of stay in hospitals in Japan. The peak average length of stay in hospitals including

chronic hospitals was close to 40 days in 1985 in Japan. After the medical insurance

system was revised in 1985, the average length of stay decreased to 33.5 days by 1996

(Fukushima & Kouno, 2000). At present, the average length of hospital stay is 20.7 days

(WAM NET, 2006). The revised medical insurance system focuses on decreasing the length of stay in hospitals to save health care costs. Hospitals have less profit in the

longer length of stay in hospitals. Discharge planning was instituted in hospitals after the

introduction of the LTCI system in 2000 (Fukushima & Ogawa, 2002; Ogawa,

Fukushima, & Gouma, 2003a; Ogawa, Fukushima, & Gouma, 2003b). The place for

treating patients has increasingly shifted from hospitals to home health care settings for

chronic care and post-acute care in Japan. Thus, there is a growing need to better

understand home-visit nursing care because of the demand for post-acute care.

Third, home-visit nursing care recently has received more national attention.

VNSs that are responsible for assisting elders were established in 1992 under Japan’s

Health Law for the Elderly. In addition, the home-visit nursing care program is also a

service that is provided under the Long-Term Care Insurance (LTCI) system (Social

Insurance Society, 2000). After the implementation of the LTCI law, the number of home

visits increased by 44 %. The number of home-visit nursing care visits was 1,078,936 in

September, 2000, and 1,552,208 in September, 2005 (Japanese Ministry of Health,

Labour, and Welfare, 2005). However, the number of VNSs has not increased to meet the

growing demand for care (Japanese Nursing Association, 2003). To further improve the

health and welfare policies for the elderly, the Ministers of Finance, Health and Welfare, 4

and Home Affairs agreed upon a new Gold Plan, on December 19, 1999, which showed

that the estimated number of VNSs needed was 9,900 facilities by 2004 (Japanese Health

and Welfare Statistics Association, 2002). In reality, there has only been a small increase

in the number of VNSs from 4,730 stations in 2000 to 4,991 stations in 2002, 5,224

stations in 2004, and 5,309 stations in 2005, according to statistics in the LTCI by the

Japanese Ministry of Health, Labour, and Welfare (2005). The increase in the number of

VNSs has stalled. At the same time, there has not been a significant increase in the

number of visiting nurses. The number of visiting nurses was 20,326 in 2000 and 22,460 in 2005 (Japanese Ministry of Health, Labour, and Welfare, 2005), an increase of 10 %.

Likewise, the Japanese Nursing Association (2003) prioritized reinforcement of human resources in home-visit nursing care and expansion of the discretionary power of visiting nurses. They have also pointed out that the current number of 5,000 VNSs is less than sufficient to provide nursing services to patients at home and that the increase in the number of VNSs has recently stalled. Although there is a need to establish more VNSs, visiting nurses are in short supply, and moreover, more visiting nurses are leaving their jobs (Japanese Nursing Association, 2004).

Many nurses in general are leaving their jobs, but the rate of visiting nurses leaving their jobs at VNSs (13.2%) is higher than that of nurses at hospitals

(11.6%)(Japanese Nursing Association, 2004). Moreover, a survey on nursing services in

VNSs by the Japanese Nursing Association (2004) showed that 42% of the VNSs identified an inadequate number of visiting nurses. The Japanese Nursing Association

(2006a) stated that the number of nurses who work in a hospital should be increased, that the number of patients for whom a nurse must care should be decreased, and the instances 5 of overnight work should be decreased in order to retain nurses and attract more to work in hospitals. However, this policy is only applicable to nurses working in hospitals.

Because it only focuses on improving the environment in hospitals, there is no policy for the retention of nurses working at VNSs, despite the great increase in the number of visits and the known deficit in the number of VNSs and visiting nurses.

Visiting nurses clearly report reasons for leaving their jobs. In the U.S.,

Ellenbecker, Neal-Boylan, and Samia (2006) showed that the reasons nurses give for leaving their jobs were the following: “too much paperwork,” too much time spent on- call on holidays and weekends, “excessive workload,” “poor benefits” and “poor salary,”

“unreasonable productivity and work expectations,” “car maintenance,” lack of respect, and so on. Moreover, Marek, Popejoy, Petroski, Mehr, Rantz, and Lin (2005) pointed out that there was no reimbursement for the extra care required to coordinate care in home health care paid by Medicaid programs in the U.S. There is an increased level of care coordination required by nurses, but there are few studies on the topic (Marek et al.,

2005).

It is likely that similar conditions exist in Japan. The salary of a nurse who works at a visiting nurse station is lower than that of a nurse who works at a hospital. According to a survey of 574 visiting nurses conducted by the Japanese Nursing Association (2004), the average basic salary for visiting nurses was 271,700 yen a month (approximately

$2,227US) (122yen = $1US). On the other hand, the average salary for hospital nurses was 338,859 yen (approximately $2,778US) as reported by the Japanese Nursing

Association (2006a). Moreover, in comparison with hospital nurses, visiting nurses have excessive workloads. While hospital nurses only work five eight-hour shifts a week, 6

many visiting nurses are on-call 24 hours a day even if they have completed five eight-

hour work days in a week. In Japan, Fujiya, Shimanouchi, and Satou (1998) point out that

there are VNSs which do not provide 24-hour care because they do not have enough

money for nurses, even though there is a need for 24-hour home-visit nursing care

services. The Japanese Nursing Association (2006b) reported that the Japanese Ministry of Health, Labour, and Welfare approved new reimbursement for emergency home visits in addition to regular home visits to facilitate VNSs to provide 24-hour care. Even after the revised reimbursement system, visiting nurses anecdotally report excessive workload, such as too much time spent on-call on holidays and weekends. Visiting nurses sometimes receive a telephone call from patients at night, in addition to having to visit patients during the day and needing to stand ready for calls from patients 24 hours a day, even on holidays, if their VNS provides 24-hour care. Thus, the workload of visiting nurses is different from that of hospital nurses.

The number of visits per visiting nurse station increased after the implementation of the new law in 2000, as the reimbursement amount per visit decreased (Ogawa, 2002) because payment system was changed. The nature of the change was reimbursement went to the time per visit from a per visit reimbursement system regardless of time. Thus, thirty minute visits were paid less than 60 minute visits. Ogawa (2002) compared the utilization of services between one year before and one year after the implementation of the LTCI law at a visiting nurse station. The number of visits for one year before was

2,271, while the number of visits for one year after was 3,253. The average reimbursement to the agency per visit before the law was 9,280.9 yen (approximately

$76US) (122yen = $1US), but the average per visit after the implementation of the LTCI 7

was slightly less, 9,081.6 yen (approximately $74US). According to another study by

Uchida (2002), the average reimbursement per visit before the law was 9,605 yen

(approximately $79US), but the average reimbursement to the agency per visit after the implementation of the LTCI was slightly less, 9,484 yen (approximately $78US) among seven VNSs. Moreover, the amount of profit for one month by the VNS was lower after the passage of the law, to 32,883 yen (approximately $270US) from 451,286 yen

(approximately $3,699US). This was profit decrease by organization.

Adding to the dissatisfaction, visiting nurses are required to spend unpaid time to coordinate care. Visiting nurses are not reimbursed for the indirect work they do once

they have completed their home visits. Although visiting nurses spend time working on

patient care between visits, they are primarily reimbursed for the actual time they spend

at the patient’s home. The Japanese Nursing Association (2005b) submitted their

opinions on the revised reimbursement to the Japanese Ministry of Health, Labour, and

Welfare. One of the opinions was that reimbursement per visit should increase, especially

because visiting nurses need extra time to coordinate care for patients with dementia,

mental illness, and terminal illness. However, the opinion was not approved and

reimbursement did not change.

According to the Japanese Ministry of Health, Labour, and Welfare (2005), 310

of 5,534 VNSs in the LTCI were closed or suspended in 2004. The VNSs closed because it was difficult for them to earn enough money to pay visiting nurses their salaries

(National Association for Home-Visit Nursing Care, 2003). Although this problem has been recently recognized, there has been little research on how Japanese visiting nurses spend their time (paid and unpaid time) and there are few studies on VNSs. One of the 8

reasons for this is that most nurses work at hospitals. Most nurses have little experience with VNSs. According to the Japanese Nursing Association (2005a), 63.3 % of nurses are working in hospitals and 22.2 % of nurses are working at clinics. Only 2.1 % of nurses are working at VNSs (Japanese Nursing Association, 2005a).

Although home-visit nursing care became much more important to at-home patients after the LTCI system started in Japan, there is a lack of research on visiting nurses in Japan. This research study proposed to fill this gap. Exploring the workload of visiting nurses might prompt discussion of whether current reimbursement is suitable for home-visit nursing care services, how visiting nurses can be reimbursed for their services, and the best way for visiting nurses to be reimbursed in the future. Also, studying the nursing work done by visiting nurses might shed light on the factors related to their job satisfaction and assess the conditions of their practice settings. Establishment of more

VNSs is needed in Japan (Japanese Nursing Association, 2003). However, there are few studies on how satisfied visiting nurses are with their jobs and how they actually work.

Conceptual Framework

The conceptual framework for this study is based on Donabedian’s (1966)

Structure-Process-Outcome (SPO) model. The SPO model describes three concepts: structure, process, and outcome (Donabedian, 1969, 1976, 1980, 1988). Donabedian’s

(1966) original study attempted to evaluate the medical care process at the physician- patient level. Later, Donabedian’s concepts were used in nursing in addition to medical outcomes (Tarlov, Ware, Greenfield, Nelson, Perrin, & Zubkoff, 1989; Kelly, Huber,

Johnson, McCloskey, & Maas, 1994). 9

Structure is defined as “the relatively stable characteristics of the providers of care” (Donabedian, 1980, p.81). The concept of structure covers human resources as well as physical and financial resources. The SPO model (Donabedian, 1988) defines process as “what is actually done in giving and receiving care” (p.1745). The concept of process includes the practitioner’s activities and the patient’s activities. Outcomes are the results of care. Donabedian (1969) states, “the evaluation of outcomes consists in the assessment of the end results of care” (p.1833). Thus, outcomes are an important dimension of evaluation. Indicators of quality that are chosen as the specific outcomes could depend on the aspect of quality being assessed. Donabedian’s (1976) model shows links in the evaluation process. The conceptual framework by Donabedian (1988) guides the selection and measurement of variables for the present study.

Concepts in the present study

The conceptual framework of the present study relied on Donabedian’s three major concepts: structure, process, and outcome. The relationships between the major concepts based on the SPO model are shown in Figure 1. The concept of structure includes provider characteristics (Donabedian, 1980). The present study focused on visiting nurses, so the concept of structure included nurse characteristics, which consisted of demographics such as age, gender, employment status, and years of nursing experience.

The concept of process encompasses the practitioner’s activities (Donabedian,

1988). In this study, process involved the means by which care is delivered in the home by the nurse and the related activities included in care provision. Thus, in the present study the concept of process dealt with all the activities involved in home-visit nursing care, which comprised both direct and indirect care: the number of visits (direct care), 10

hours (direct care and indirect care), types of visits (direct care), and types of indirect care.

Productivity is a measure of process, and the components of productivity in

relation to nursing, presented below, are complex. There are three primary ways of

measuring activity: “task,” “role,” and “service delivered” (Office of Government

Commerce, 2005). In this study, productivity was measured according to the “service

delivered.” Productivity was measured by “a ratio of output to input” (p.9), but, as the

discussion in Chapter II will show, the definition and quantification of input and output

have not been satisfactorily conceptualized to measure the productivity of nursing

(Jelinek & Dennis, 1976). Levy (1979) emphasized the need to establish some workable productivity standards because there was no consensus on the concept of the productivity of visiting nurses. The present study required that a suitable concept of productivity for

Japanese VNSs be established.

Japan partially solves this problem with their classification of visits. In Japan,

home-visit nursing care services are primarily reimbursed on a per visit basis. However,

types of reimbursement per visit in the long-term care insurance system are classified

according to duration of the visit: less than 30 minutes, from 30 less than 60 minutes, and

from 60 less than 90 minutes (Social Insurance Society, 2000). For visits that exceed 90

minutes, there is no additional reimbursement. Thus, both the number of visits and the

hours that visiting nurses directly care for patients at home are significant in Japan and

should be included in the calculation of productivity in the present study.

Also, nonproductive hours in addition to visits should be included in the

productivity formula. Visiting nurses spend time not only visiting, but also preparing for 11 visits, in travel, charting, calling physicians, and so on. The required time for patients consists of direct and indirect care (Fujiya, Shimanouchi, & Kamei, 1999). Indirect care such as coordination and administration is important in home-visit nursing care.

Power (1987) uses three categories of nursing activity: “direct (visiting),” “special

(clinic, beeper, school programs),” and “indirect (case conferences, staff meetings, etc.)”

(p.41). In her formula, total hours include direct and indirect hours but exclude special hours defined as “clinic, beeper, and school programs” (p.41). However, the present study proposed that total hours included all the hours that visiting nurses worked. In the present study, indirect care hours were defined as all hours except direct care hours for visits. The formulas utilized in the present study to determine productivity for home health care settings were adapted from Power’s (1987) formulas. The formulas used in the present study are as follows:

Total hours (direct* and indirect**)÷Total number of visits (direct)=Hours per

visit

Total hours (direct and indirect)÷working days÷Hours per visit= Visits per day

*direct care hours = hours spent by visiting nurses in the patient’s home

**indirect care hours= the total number of hours worked excluding direct care

Thus, in this study, total number of hours included both reimbursable and non- reimbursable hours. Measuring the total hours that home-visit nurses work (direct and indirect) will allow the researcher to explore the relationship between productivity as process and job satisfaction as outcome. 12

Outcomes are effects from the process of care (Donabedian, 1980). Donabedian

(1980) divides the concept of outcome into two categories: client-related outcomes and practitioner-related outcomes. Likewise, for the assessment of effectiveness, Freeborn and Greenlick (1973) proposed measuring two categories of effectiveness: technical effectiveness and psychosocial effectiveness. Psychosocial effectiveness can be measured as patient satisfaction and provider satisfaction (Freeborn and Greenlick, 1973).

Moreover, Ervin & Jones (2000) show staff/consumer satisfaction as a component of outcome. Because this study focused on practitioner-related outcomes, outcomes were defined as provider satisfaction. The present study focused on the satisfaction of visiting nurses with their jobs.

In the present study, job satisfaction was measured by the Nursing Work Index-

Revised (NWI-R) and a single item indicator for overall job satisfaction. The NWI-R provided a better measurement than the use of only one question that measured the overall job satisfaction. The NWI-R by Aiken & Patrician (2000) is a modification to the

Nursing Work Index (NWI) by Kramer & Hafner (1989) for measuring nurses’ job satisfaction and perception of quality of care. The four subscales in the NWI-R include

“autonomy,” “control over the practice setting,” “nurse-physician relationship,” and

“organizational support” (Aiken and Patrician, 2000). Tullai-McGuinness, Madigan, &

Anthony (2005) used two subscales of the NWI-R, “autonomy” and “control over the practice setting,” in order to measure the degree of autonomy experienced by nurses in home health care agencies in the U.S. Autonomy is one of the most important determinants of job satisfaction for nurses working in home health care in the US (Lynch,

1994). Thus, these two subscales are important in the present study. 13

Also, the other two subscales in the NWI-R, “nurse-physician relationship” and

“organizational support,” are of great significance for job satisfaction. A survey of home care nurses by Ellenbecker & Byleckie (2005b) confirms that “Relationship with physician” and “Organizational components” as well as autonomy are important for job satisfaction. Thus, all four subscales of the NWI-R were used to measure job satisfaction in the present study.

The proposed variables were nurse characteristics and productivity, which are thought to influence job satisfaction. Based on the S-P-O model, the conceptual framework of the present study is shown in Figure 1.

Structure Process Outcome Nurse Productivity Job characteristics Productivity will be calculated from the satisfaction -Age formula below, using the data of *time -Overall job -Gender spent on home-visit nursing care: satisfaction Hours per visit= Total hours (direct and -Employment -NWI-R status indirect)÷ Total number of visits (direct) subscales -Years of Visits per day = Total hours (direct and experience as a indirect) working days hours per visit nurse ÷ ÷

*Time spent on home-visit nursing care -Number of visits (direct care) -Hours (direct care and indirect care) -Types of visits (direct care) Types of indirect care

Figure 1. Conceptual framework of the present study

The bold and italicized terms above refer to the constructs; the bold terms refer to the concepts and the plain text terms refer to the measures.

Definition of Terms

The following definitions were used in the present study.

Visiting nurse. A nurse who cares for patients living at home.

Home-visit nursing care. Nursing service provided by visiting nurses for patients

living at home.

Visiting nurse station (VNS). An agency that employs visiting nurses who provide

patients living at home with nursing services.

Research Questions

The research questions of the study are as follows:

Research Question 1: Is “structure” associated with “outcome”?

- Are nurse characteristics associated with job satisfaction?

Research Question 2: What is the productivity of Japanese visiting nurses?

Research Question 3: Is “structure” associated with “process”?

- Are nurse characteristics associated with home-visit nursing care

productivity?

Research Question 4: Is “process” associated with “outcome”?

- Is home-visit nursing care productivity associated with job satisfaction?

Research Question 5: Which structure and process variables are most important in

explaining job satisfaction? 15

Significance to Nursing Science and Practice

This study is important to the discipline of nursing. Research in nursing is important to develop a relevant body of knowledge and to acquire knowledge for improving the practice (Polit & Hungler, 1999). In other words, the study should contribute to both building the body of knowledge as nursing science and using the knowledge for practice in nursing. This present study is significant to both nursing science and practice.

Nursing Science

Nursing science is defined by Barrett (2002) as “being broad enough to encompass all disciplinary knowledge” (p.56). Moreover, “Nursing science is an identifiable, discrete body of knowledge comprising paradigms, frameworks, and theories” (Daly, Mitchell, Toikkanen, Millar, Zanotti, Takahashi, et al., 1997, p.10). The body of knowledge should show the profession’s thinking and give direction to develop science and theory in the discipline (Burns & Grove, 2005). According to Chinn &

Kramer (2004), knowing is different from knowledge: “The term knowing refers to ways of perceiving and understanding the self and the world. The term knowledge refers to knowing that is in a form that can be shared or communicated with others” (Chinn, et al,

2004, p.2). Thus, the study helped to explain nursing phenomenon in VNSs in Japan as knowledge contributing to nursing science.

Home-visit nursing care has received more national attention since the implementation of LTCI law in 2000. However, there is little research on home-visit nursing care because it is still in the developmental stage. The present study was designed to develop the knowledge for nursing practice in VNSs in Japan. The significance to 16

nursing is based on building the knowledge of nursing science. The study focused on the

workload of visiting nurses in Japan. The S-P-O model guided the relationships between

nurse characteristics, productivity, and job satisfaction. The results of the study will

provide an explanation and empirical evidence for how productivity is related to job

satisfaction.

Nursing Practice

According to Reed (1996), “Nursing knowledge is developed in practice as well as for practice” (p.30). Knowledge is linked to practice. Development of nursing knowledge acquired in the present study will be significant to nursing practice in VNS settings in Japan.

Although more studies of the workload of visiting nurses in Japan will be required, the findings of this study are expected to provide essential information for nurses to understand the phenomena of home-visit nursing care in terms of the relationships between nurse characteristics, productivity, and job satisfaction. The nursing administrator may be able to identify the factors influencing job satisfaction in the environment in VNSs.

Implication for policy in Japan. The findings of the study are also important for the development of policies in the home-visit nursing care settings. Based on the results of the study, policymakers know more how visiting nurses work and how satisfied nurses are about their jobs, which may facilitate discussion of whether current reimbursement is suitable for home-visit nursing care services. Because of poor reimbursement and the reported workloads, visiting nurses may not remain in their positions and VNSs may not be available in Japan to meet the rising demand. The findings may suggest ways that 17 could improve visiting nurses’ work environments. A goal of this study is to develop knowledge and to facilitate practice using the knowledge obtained from the study. Nurses play a significant role, not only in hospital settings, but also in VNS settings in Japan.

The present study is important for building nursing science in VNS settings, which may facilitate improving the practice environment for visiting nurses.

Chapter II

Review of the Literature

A review of the relevant literature is “an analysis and synthesis of research sources to generate a picture of what is known and not known about a particular situation or research problem” (Burns and Grove, 2005, p.750). This chapter begins with the results of a literature search for research articles on the workload of visiting nurses, which are analyzed in three sections: structure, process, and outcome, using the S-P-O framework, as stated in Chapter I, as a guide. Then a summary of what is known and what is not known is presented.

First, outcome, as conceptualized for the present study, focuses on research on job satisfaction among home care nurses. This first part shows relationships between job satisfaction and nurse characteristics, such as age, gender, employment status, and years of experience. Second, process, as conceptualized for the present study, includes productivity and time spent in home visit-based nursing care. This second part presents relationships between productivity and nurse characteristics. Finally, the literature review from these parts is summarized to identify gaps in the current knowledge.

Job satisfaction

Job satisfaction has a significant impact on employee retention (Neal, &

Ellenbecker, 2004). Many studies of nurse job satisfaction have been conducted in hospital settings (Mueller and McCloskey, 1990; Whitley and Putzier, 1994), but research on job satisfaction has only recently begun to be conducted in home health care settings

(Ellenbecker, 2001; Ellenbecker & Byleckie, 2005a & 2005b; Navaie-Waliser, Lincoln, 19

Karuturi, & Reisch, 2004; Smith-Stoner, 2004). Table 1 contains a summary of the relevant research on the relationship between job satisfaction and nurse characteristics.

Table 1

A summary of the relevant research: Job satisfaction and nurse characteristics

Authors Purpose of the Sample and Instruments Results (Year) study Settings Anthony & To examine job 529 home care Questionnaire from The highest response to “what do you like most Milone- satisfaction. nurses in previous literature about home care” was “flexibility”(19%), Nuzzo (2005) Connecticut. developed by the followed by “one-on-one patient care”(18%), Connecticut and “independent practice”(16%). There was no Association for Home comparison done between nurse characteristics Care (CAHC) Human and the result of job satisfaction. Resource Special Interest Group.

Armstrong- To examine job 1044 community Questionnaire from CCAC nurses (mean=3.66 [ranged from 1 to 5]) Stassen & satisfaction among health nurses in previous literature. were significantly less likely to be satisfied with Cameron public health public health, their job than public health nurses (mean=3.83) (2005) nurses, home care home care, and and home care nurses (mean=3.81) (F=3.39, nurses, CCAC community care p<.05). nurses access center (CCAC) agencies in Ontario, Canada.

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Elder, To examine hassles 57 employees as The Hassles Scale and The highest ranked uplifts were, according to Wollin, and uplifts registered nurses the Uplifts Scale. percentage of respondents, were “a patient Hartel, and personal cooperates with my instructions”(98.2%) and “I Spencer, & carers in know the patient well”(98.2%). The highest Sanderson residential (n=20) ranked hassles were “a person wants too much (2003) and community attention”(61.4%), “a patient is rude”(61.4%), (n=37) healthcare and “other healthcare providers trivialize settings in patient problems”(61.4%). Brisbane, Queensland, Australia.

Ellenbecker To identify the 254 nurses from 4 A version of the Home The average satisfaction score (21-item 5-point (2001) level of job home health Health Nurses’ Job Likert scale) was 82.17 (38-104). Cronbach’s satisfaction of agencies in the Satisfaction (HHNJS) alpha for overall reliability was .80. There were home health care northeast, Scale with 21 items on no differences in the satisfaction scores based nurses southwest, and the 5-point Likert scale on nurse and agency characteristics: years of western United (after the pilot study to experience, full-time or part-time status, job States. develop the HHNJS specialty (general or specialty), education, with 30 items from position (direct care or supervisor), and type of previous literature). agency. The nurses in the western United States had significantly lower satisfaction than the nurses in the southwest and northeast (Chi- Square=18.58; p<.01) when satisfaction level was divided into three (high [104 to 87.5], medium [67.4 to 79], and lower [78.5 to 38]).

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Ellenbecker To develop the 340 home A version of the Home There was good criterion-related validity, the & Byleckie Home Healthcare healthcare nurses Healthcare Nurses’ Job correlations (.79) between the HHNJS and the (2005a) Nurses’ Job from 11 agencies Satisfaction (HHNJS) MMSS. The nine factors contributing to job Satisfaction Scale. in Maryland, scale with 32 items on satisfaction emerged from the factor analysis: Virginia, the 5-point Likert scale. autonomy, profession, relationships with peers, Michigan, The McCloskey relationships with physicians, characteristics of Tennessee, Satisfaction Scale agency, stress, flexibility in work scheduling, Oregon, and the (MMSS). control of work activities, and benefits. There District of was no comparison done between nurse Columbia. characteristics and the indicators of job satisfaction.

Ellenbecker To identify the 340 home health A version of the Home The three most satisfying factors were & Byleckie factors related to care nurses from Healthcare Nurses’ Job “relationship with the patient”(mean=4.52), (2005b) variability in home 10 agencies in 5 Satisfaction (HHNJS) “autonomy and professional health care nurses’ states (Maryland, scale with 30 items on pride”(mean=4.26), and “cohesion among job satisfaction. Virginia, the 5-point Likert scale. peers”(mean=4.16). There was no association Michigan, with nurse characteristics: gender, age, years of Tennessess, nursing experience, education, family income, Washingtron) and benefits, and dependents. the District of Columbia.

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Ellenbecker, To validate the 2,273 nurses from The open-ended A typical nurse response to “What nurses like et al. (2006) Home Healthcare 123 home (qualitative) questions. about their jobs?” was “autonomy and Nurses Job healthcare independence,” “relationship with patients,” Satisfaction Scale agencies in New “relationship with organization,” and so on. The (HHNJS). England. HHNJS scale was consistent with the analysis of the qualitative data. There was no comparison done between nurse characteristics and the indicators of job satisfaction (the HHNJS).

Flynn (2003) To identify agency 403 home care Items in the survey The three most important agency traits were traits that are nurses in 48 states were three open-ended “support for education,” descriptions of “a important to job across the U.S. questions. knowledgeable and supportive front-line satisfaction and (Participating nurses supervisor,” and “dedication to quality care.” nurses’ professional simply listed agency More than 56 % indicated “support for practice. traits they think most education.” There was no comparison done important to job between nurse characteristics and the agency satisfaction and nurses’ traits that are important to job satisfaction. professional practice).

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Flynn (2005) To investigate traits 403 home care The 49-item NWI-R on Nurses rated the importance of each trait in that are important nurses from all the 4-point scale supporting their home care nursing practice of job satisfaction. six geographical ranging from 1 (mean range=3.81to2.09). The top three agency regions of the (strongly disagree that traits with highest mean were “a supervisory U.S. the trait is important) to staff that is supportive of nursing”(mean=3.81), 4 (strongly agree that “working with nurses who are clinically the trait is important). competent” (mean=3.78), and “not being placed in position of having to do things that are against my nursing judgment”(mean=3.78). There was no comparison done between nurse characteristics and traits that are important to job satisfaction.

Flynn, To investigate the 403 home care 49 items of the Nursing Approximately 80 percent of the nurses agreed Carryer, & nursing work nurses from 48 Work Index-Revised or strongly agreed with 47 items on the NWI-R. Budge (2005) environment among states in the U.S., (NWI-R). Total mean scores (170.61) on the NWI-R hospital-based, 320 district nurses among home health care nurses in the U.S. were home care, and in New Zealand, significantly lower as compared with the other district nurses. and 669 hospital- two groups: N.Z. district nurses (175.90) and based nurses U.S. hospital-based nurses (176.44). pooled existing secondary data in the U.S.

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Flynn & To find attributes of Seven focus Focus group discussion The following six categories were identified as Deatrick home care agencies groups. A total of verbatim. attributes of home care agencies: “extensive (2003) as traits that are 58 nurses in 6 preceptor based orientation,” “an organized & important of job home health care supportive office environment,” “reasonable satisfaction. agencies in the working conditions,” “accessible field Mid-Atlantic security,” “competent & supportive region of the U.S. management,” and “a patient-centered mission and vision.” These attributes were similar to those described in both hospital settings and the magnet hospital. There was no comparison done between nurse characteristics and attributes that are important to job satisfaction.

Lynch (1994) To examine job 66 home health McCloskey/Mueller The majority of nurses were satisfied with satisfaction of care nurses from Satisfaction Scale flexibility in scheduling work hours (85%), the home health care 3 agencies (two in (MMSS). hours that nurses work (78 %), and salary nurses Pennsylvania and (71 %). There was no comparison done between one in New nurse characteristics and job satisfaction. Jersey).

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Moore & To compare the 67 home health The job satisfaction There was no significant difference between the Katz (1996) levels of stress nurses from 3 scale developed by the levels of stress in acute care nurses and home among home health agencies in the University of Michigan health nurses. There were positive relationships nurses with acute Midwest and 71 Survey Research between job satisfaction and self-esteem care surgical nurses acute care Center. The Rosenberg (r=.40), job satisfaction and intimacy (r=.39), and to examine the surgical nurses Self-Esteem Scale. The and self-esteem and intimacy (r=.56). There levels of stress, from a prior Social Intimacy Scale. was a negative relationship between job self-esteem, study. Items adapted from the satisfaction and stress (r=-.36). There were no intimacy, and job Nursing Stress Scale. significant differences between the levels of satisfaction among stress, self-esteem, and job satisfaction for home health nurses. nurse characteristics (gender, age, years of experience, educational level, and marital status). There was a significant difference between the levels of intimacy for the single/separated/divorced (mean=57.24) and married group (mean=52.10).

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Navaie- To find factors 188 home health Questionnaire for The top three factors related to job satisfaction Waliser, related to job staff, including 52 information on were adequate supports from the office (mean Lincoln, satisfaction. nurses (RNs and perceived job elements, scores ranged between 3.71 and 4.55), the Karuturi, & LPNs) at a large etc. reputation of the agency (mean scores ranged Reisch home health care between 3.73 and 4.43), and relationships with (2004) agency in New patients (mean scores ranged between 3.55 and York. 4.25) on a scale of 1 (least important) to 5 (most important). Variables ranked as the least important factor related to job satisfaction were educational and promotional opportunities. Newer employees (those employed less than 1 year) had more positive relationship with supervisors than staff who had been employed more than 1 year. (The relationship with supervisors is an important indicator of job satisfaction [Navaie-Waliser, et al., 2004], so longer time employees may be less satisfied with relationship with supervisors.) Also, senior employees (those employed for 6 or more years) ranked highly “recognition and acknowledgement” as an important indicator of increasing job satisfaction.

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Smith-Stoner To determine the 841 home care 16 close-ended and 3 81% of respondents identified adequate staff (2004) degree of agency nurses from an open-ended questions during regular hours, but only 20% of traits that are online survey. that were developed respondents identified adequate staff outside of important to job from previous articles. regular hours. Staff nurses were the least likely satisfaction. to remain in home care: 21% of the clinical staff had decided not to remain in home care. Half of the respondents said that administrators had adequate communication skills with staff. There was no comparison done between nurse characteristics and traits that are important to job satisfaction.

Table 1 (continued).

Authors Purpose of the Sample and Instruments Results (Year) study Settings Tullai- To measure the 82 staff RNs of Participation in There were few significant relationships McGuinness, exercise of 11 home health Decision Activities between nurse characteristics, such as RN Madigan, & autonomous care agencies in Questionnaire(PDAQ), experience and experience in home health, and Anthony practice in home Ohio. Nursing Work Index- nurses’ clinical autonomy and organizational (2005) health care, and to Revised (NWI-R), and autonomy. (Correlations between RN measure how Global Appraisal of experience and control over practice [r=.09]; nursing Autonomous Practice control over practice and HHC experience characteristics were (GAP). [r=.11]; RN experience and control over setting related to nurses’ [r=.10]; HHC experience and control over clinical autonomy setting [r=.10], using PDAQ, from Tullai- (control over McGinness [2003]). There was a small negative practice decisions) correlation between certification and control and organizational over practice (r= -.27), using the NWI-R. autonomy (control Overall, RNs perceived more clinical autonomy over practice (mean=3.32) than organizational autonomy setting decisions). (mean=3.02), using the NWI-R (possible range, 1-4).

Job satisfaction

There is a relatively limited amount of research on job satisfaction among home

care nurses. It is difficult to draw conclusions as different instruments were used to

measure job satisfaction in studies from review of the literature. There are two different

studies using the NWI-R in home care settings. Research conducted by Flynn, et al.

(2005) used 49 items of the NWI-R and showed the NWI-R total mean (170.61) among

home care nurses in the U.S. Subscales were for the following: autonomy (total

mean=18.37), control (total mean=24.83), physician relationships (total mean=10.65),

and organizational support (total mean=32.24). Thus, there is support to use the four

subscales of the NWI-R in home care settings as in hospital settings. In another study

among home care nurses, Tullai-McGuinness et al. (2005) used two subscales of the

NWI-R item: autonomy (practice; item mean=3.32) and control (over the practice setting;

item mean=3.05). (The scoring systems were different between the two studies, thus it is

difficult to compare sub-scale means between the studies.) According to Flynn et al.

(2005), home health care nurses in the U.S. are significantly less satisfied (total

mean=170.61) than district nurses (175.90) in New Zealand and hospital nurses (176.44)

in the U.S.

Ellenbecker (2001) conducted a pilot study with 25 home healthcare nurses to develop the Home Health Nurses’ Job Satisfaction (HHNJS) scale with 30 items from previous literature. Then, a version of the HHNJS with 21 items on the 5-point Likert

scale was used to examine job satisfaction (Ellenbecker, 2001). The average total job

satisfaction score was 82.17 (38-104). Cronbach’s alpha for overall reliability was .80

(Ellenbecker, 2001). Ellenbecker (2005a) developed a new 32-item version of the Home 31

Healthcare Nurses’ Job Satisfaction Scale (HHNJS) and showed good criterion-related validity, the correlations (.79) between the HHNJS and the Mueller and McClockey

Satisfaction Scale (MSSS). In another study, Ellenbecker (2005b) used the 30-item

HHNJS scale on the 5-point Likert scale. The HHNJS is the only instrument to measure

job satisfaction among home health care nurses (Ellenbecker, 2001). However, the

HHNJS is still in development and has not been translated to Japanese.

There are two main studies that explain job satisfaction among home care nurses

(Flynn, 2003; Ellenbecker and Byleckie, 2005b). Flynn (2003) showed the 10 agency

characteristics as most valuable to home care nurses were: “education, manager, quality

care, administrative support, communication, flexible schedules, salary and benefits,

reasonable workload, input to decision making, and adequate staffing” (p.779).

Ellenbecker et al. (2005b) showed nine factors representing job satisfaction: “relationship with patients, autonomy and professional pride, cohesion among peers, relationship with physician, organizational components, salary and benefits, autonomy and flexibility in

hours of scheduling, autonomy and control of work activities, and stress and workload”

(p.779). Thus, there is consistency in the characteristics that are valuable to home health

care nurses and factors related to job satisfaction among home health care nurses,

specifically autonomy, organizational support, salary, and benefits. For the present study,

measuring job satisfaction that encompasses the above variables may facilitate improving

the environment in practice for visiting nurses. Also, it may lead to policies to attract and

retain visiting nurses. 32

Relationship between job satisfaction and nurse characteristics

There has been little examination of the relationships between job satisfaction and nurse characteristics because most studies presented only descriptive information of nurse characteristics. Most studies in this area of research have not examined the relationship between nurse characteristics and job satisfaction (Anthony et al., 2005; Ellenbecker et al., 2006; Ellenbecker et al., 2005a; Flynn, 2003; Flynn, 2005, Lynch, 1994).

Some research shows no relationships between job satisfaction and nurse characteristics such as: gender (Ellenbecker, et al., 2005b; Moore, et al., 1996), age

(Ellenbecker et al., 2005b; Moore et al., 1996), years of experience (Ellenbecker, 2001;

Ellenbecker et al., 2005b; Moore et al., 1996), employment status (Ellenbecker, 2001); education (Ellenbecker, 2001; Ellenbecker et al., 2005b; Moore et al., 1996); marital status (Moore et al., 1996); job specialty, position, and type of agency (Ellenbecker,

2001); family income, benefits, and dependents (Ellenbecker et al., 2005b). Also, Tullai-

McGuinness et al. (2005) found few significant relationships between job satisfaction

(autonomy) and nurse characteristics, such as RN experience and experience in home health care.

However, some studies show significant relationships between job satisfaction and characteristics. The studies that have examined the relationships have had mixed results. Those studies finding significant relationships include work by Tullai-

McGuinness et al. (2005) and Ellenbecker (2001). Tullai-McGuinness found that there was a small negative correlation between specialty certification and control over practice

(r= -.27), using the NWI-R. Also, Ellenbecker (2001) found that nurses in the western

United States have significantly lower satisfaction than those in the southwest and 33

northeast when satisfaction was divided into three levels (high [104 to 87.5], medium

[67.4 to 79], and lower [78.5 to 38]). Moreover, Moore et al. (1996) found that there was a significant difference between the levels of social intimacy for the single/separated/divorced (mean=57.24) and married group (mean=52.10). Social intimacy was defined as “the sharing of an individual’s appraisal of stress, the unloading

of troublesome thoughts, and the opportunity to clarify subjective reality without being

guarded” (Moore et al., 1996, p.966). No other studies have examined this relationship.

Navaie-Walise, et al. (2004) found newer employees (those employed less than one year) had more positive relationships with supervisors than staff who had been employed more than one year. The relationship with supervisors is an important indicator of job satisfaction (Navaie-Waliser et al., 2004), yet it is not clear why longer term employees may be less satisfied with their relationships with supervisors. Also, the study showed that more senior employees (those employed for six or more years) ranked highly

“recognition and acknowledgement” as an important indicator of increasing job satisfaction (Navaie-Waliser et al., 2004). Thus, age and years of experience may be associated with job satisfaction. For the present study, nurse characteristics will be included to determine whether there are relationships between nurse characteristics, productivity, and job satisfaction in Japanese visiting nurses.

Productivity

This section extracts from the relevant literature only research on the relationships between productivity and nurse characteristics. Table 2 contains a summary of the relevant research. 34

Table 2

A summary of the relevant research: Productivity and nurse characteristics

Authors Purpose of Sample and Instruments Results (Year) the study Settings Feldman & To identify A total of 528 Start Patient Higher productivity Gurian the cases for the Classification correlated with higher (1988) relationship 436 patients Scale percentage of staff between from 12 home (SPTCLASS) nurses experienced in productivity care agencies home care (rho=.51). and staff in one experience. Midwestern state.

Hedtcke, To examine 260 nurse- A daily The average number of MacQueen, the average days at the activity log. visits per day was 4.8— & Carr number of Visiting that is productivity (1992) visits per Nurse (visits/day) for all day. Association nurses. The productivity of Chicago by fee-for-visit nurses (VNA-C). was 4.0 visits/day, while that by salaried nurses was 5.1 visits/day.

Relationship between productivity and nurse characteristics

There is only one study that examined the relationship between productivity and nurse characteristics. Feldman and Gurian (1988) found that higher productivity correlated with a higher percentage of staff nurses experienced in home care before their current home care job (rho=.51). Staff nurses who had more experience in home care had higher productivity; thus, years of experience in home care might be related to productivity. However, it is not possible to draw strong conclusions from just one study.

In addition, although a survey conducted by Hedtcke, MacQueen, and Carr (1992) provided descriptive data, it showed that payment status may be related to productivity.

The productivity of fee-for-visit nurses was 4.0 visits/day, while that of salaried nurses 35

was 5.1 visits/day. In the study, a statistical analysis was not conducted to compare the difference although a difference of 1.1 visits/day is substantively different. Thus, employment status may be related to productivity.

Relationships between productivity and job satisfaction

There is no research on the relationships between productivity and job satisfaction.

Most studies in productivity have not used a statistical analysis: only descriptive

information is shown in the following studies.

Productivity

There are primarily two formulas of productivity in home health care found in the

literature. Levy (1979) defined productivity in home health care as “the number of visits

per nurse per day” (p.24). Rozelle (1977) also stated that productivity can be measured as

“visits per nurse per day” (p.23) in home health care. Power (1987) points out that

Rozelle’s formula does not include nonproductive hours (the hours spent in indirect care),

and suggests that the number of nonproductive hours should be included in a productivity

statistic. Power (1987) offers a more nuanced formula for calculating productivity:

“Total hours (direct & indirect) ÷ total visits = hours/visit

Hours per work day ÷ hours/visit = visits/day” (p.41).

For the purposes of this study, however, Power’s model must be further refined to include the actual complexities involved in home-visit nursing care. Levy (1979) , for instance, pointed out that productivity will be affected by several factors: “geography,”

“availability of public transportation,” “paperwork,” “severity of the patient’s condition,”

“time for in-service,” “illness,” “vacations,” “leaves of absence,” “levels of experience,” 36

and so on. Likewise, Sullivan & Decker (1992) agree that the concept of productivity

(which was originally developed for industry) can be applied to nursing and measured as

a ratio, but they state that the model for nursing is complicated. They propose that

productivity be calculated as “Required hours of care/Nursing hours paid” (p.85) in

nursing management information systems (Sullivan & Decker, 1992). Sullivan and

Decker’s model is appropriate for a hospital setting, but in home health care there is

generally a discrepancy between the required hours of care and the nursing hours paid.

Levy (1979) emphasized the need to establish some workable productivity standards because there was no consensus on the concept of the productivity of nurses.

However, researchers agree that the productivity concept (which was originally developed for industry) can be measured as a ratio (Sullivan & Decker, 1992). The conceptual model for nursing is complicated, but research studies suggest two formulas for productivity in home health settings.

Rozelle (1977) stated that productivity can be measured as “visits per nurse per

day” (p.23) in home health care. Also, Levy (1979) defined productivity in home health

care as “the number of visits per nurse per day” (p.24). Moreover, Harris (1989) used

“Number of visits during period / Number of days available for visiting” (p.67) as the productivity formula. However, Power’s (1987) productivity formula is not the same as the formulas of the above three researchers. Power (1987) offers: “Total hours (direct &

indirect) ÷ total visits = hours/visit” and “Hours per work day ÷ hours/visit = visits/day”

(p.41). Her formula includes the indirect hours in addition to visits.

There is little published research using these formulas. Levy (1979) studied the productivity of seven different agencies. He concluded that the average productivity of all 37

seven agencies was 5.6 visits/nurse/day. This number is useful to make comparisons between the average productivity of one agency and the average productivity of all

agencies. The average productivity of nurses in the individual agencies ranged from 4.9

to 6.4 visits per nurse per day.

According to Banfield (1987), the national productivity standards for a registered

nurse in home health was 5.7 visits/day in December of 1985. This number is similar to

that of the average agency productivity by Levy (1979). In Banfield’s (1987) article,

national productivity standards in hospital home health were as follows: registered nurse,

5.7 visits/day; psychiatric nurse, 3.4 visits/day; and hospice nurse, 2.9 visits/day.

Rozelle (1987) used the same formula to compare productivity among nursing

and other health professions, such as physical therapy, occupational therapy, speech

therapy, and home health aids. The productivity (visits/day) of nursing was 5.7, the

productivity of physical therapy was 4.5 and that of occupational therapy was 3.7.

Spoelstra (1988) analyzed productivity from data (a sample of 321) of a

nationwide survey. While the average productivity expectation was 5.2 visits per day, the

average productivity was actually 5.02 visits per day. Later, Spoelstra (1996) compared

productivity in 1987 and in 1996. While the number of actual visits per eight-hour

workday was 5.02 in 1987, it was 5.73 in 1996. Thus, she showed that productivity

(actual visits per 8-hour workday) increased from 1987 to 1996.

Harris (1989) conducted a project to increase productivity and to decrease office

time because reimbursement, at that time, was made on a per-visit basis. The project

results indicated an increase in productivity from 5.4 to 5.8 (average number of visits per

nurse per day) and a decrease in the percent of time nurses spent in the office from an 38 average of 24% to 19% after one year. Humphrey (2002) questioned whether measuring productivity as “x number of visits per clinician per day (or week)” was appropriate to home health care after the introduction of the payment change to a prospective payment system (PPS) in 2000.

The research shows that numbers of productivity from the above articles were all similar at 5.7 visits/day, the national productivity standards of the U.S. (December 1985) for a registered nurse in home health (Banfield, 1987). There are several limitations to these productivity standards. First is the 20 year time span between 1985 and the present.

In addition, a visiting nurse has other activities during the work day that are not visit based.

Storfjell (1989) stated that “Customarily, productivity in home care has been measured by the number of home visits made per day” (p.61), but pointed out nondirect care time was removed from the calculation. She showed the proportion of time composed of “nonvisit-related time” and “visit-related time.” “Nonvisit-related time” included documentation (20.5%), nonvisit coordination (14%), and travel (20.5%).

“Visit-related time” included assessment (15%), education (9%), physical care (8%), psychosocial care (8%), and visit coordination (5%). Thus, the proportion of time related to nonvisit work was larger than the time spent on visits in this report.

Benefield (1996) conducted factor analysis from 35 items determined by interview and Delphi analysis to understand nursing practice related to productivity of nurses in the home health setting. From the results of the factor analysis, the 35 items of productivity for nurses in home care were divided into 7 types: “client/family management,” “practice management,” “knowledge/skill maintenance,” 39

“communication,” “nursing process,” “written documentation,” and “home health care

Thus there is evidence that the activities of visiting nurses involve not only direct care and but also indirect care in a day. When calculating productivity, a calculation that includes total hours (direct and indirect) is better than using only visits per day.

Power (1987) introduced a worksheet to determine nurses’ weekly productivity and how to calculate productivity. Power’s formula for calculating productivity is shown in Table 3. Power’s worksheet makes obvious the decrease from 3.75 (visits/day) in month one to 2.51 in month two. It is important to include total hours (direct & indirect) when calculating productivity to understand differences. 40

Table 3

Example of calculating productivity by Power’s (1987) formulas (p.41)

Month 1 Month 2

Total hours worked 1000 1000

Hours per day worked 7.5 7.5

Total productive hours 750 500

Total nonproductive hours 250 500

Total RN visits made 500 335

Total hours÷total visits=hours/visit 1000÷500=2.00 1000÷335=2.98

Hours per work day÷hours/visit=visits/day 7.5÷2.00=3.75 7.5÷2.98=2.51

* Power’s calculation was not based on actual statistics.

There is no research on the productivity in the home care setting in Japan.

Power’s (1987) formula of productivity which includes the number of nonproductive hours as well as visits will be used to understand the workload of visiting nurses in Japan.

The biggest limitation to this body of research is its age (1970s and 1980s) and that it was undertaken in the US versus Japan. Since this time, the US system of reimbursement for home health care has changed several times, most recently in 2000 with the introduction of the Prospective Payment System by Medicare, the largest payer

for home health care in the US. Thus the above results need to be viewed cautiously

although the formulas are still applicable. 41

The formulas utilized in the present study to determine productivity for home

health care settings are adapted from Power’s (1987) formulas. The formulas are as

follows:

Total hours (direct* and indirect**)÷Total number of visits (direct)=Hours per visit

Total hours (direct and indirect)÷working days÷Hours per visit= Visits per day

*direct care hours = hours spent by visiting nurses in the patient’s home

**indirect care hours= the total number of hours worked excluding direct care

Time spent in home-visit nursing care

Time studies are important for measuring productivity, using the above formulas for the present study. Recent studies are available that focus on home-visit nursing care; however, studies on the time distribution factor involved are lacking. There is little

research on time studies of home health direct and indirect care. Table 4 contains a

summary of the relevant research on time studies. 42

Table 4

A summary of the relevant research: Time spent in home-visit nursing care

Author (Year) Purpose of the Sample and Results study Settings Adams & To discover 2,788 home There is a high correlation (r = .96) Michel (2001) the correlation health between number of visits and total between episodes of direct care time. There are moderate numbers of care in 4 correlations (r = .65; r = .63) between visits, length home health number of visits and length of the of the home agencies in home health episode, and between health episode, the northwest total direct care time and length of the and total direct United home health episode. care time. States.

Adams, To examine 2,788 home Direct care time Michel, De direct care health (mean=505.7minutes) in rural areas Frates, & time of rural episodes in 4 was greater than that (mean=420.7) in Corbett versus urban home health urban areas (p<.001). These studies (2001) patients by agencies focused on only direct care. It is home health (HHAs) in unclear how visiting nurses spent nurses. central and indirect care. eastern Washington.

Brooten, To measure 85 high risk APN spent total mean 51.3 hours per Brooks, time spent by pregnant woman on prenatal care. Mean times Madigan, & advance women by setting spent by APN are the Youngblut practice nurses required following: in the clinic (957.1 (1998) (APNs). home care by minutes), charting (772.2 minutes), APNs. home visits (548.6 minutes), telephone time (332.8 minutes), travel time (289.7 minutes), hospital visit time (176.9 minutes). Home care services have been measured by number of visits, but Brooten, et al. (1998) suggested that administrators may consider time spent as additional measurements.

Table 4 (continued).

Author (Year) Purpose of the Sample and Results study Settings Fukaya, To identify 210 clients The frequency of visits was related to Okabe, & factors related and 80 nurses the client’s health condition (mean Tukamoto to the of 10 home visits in good status group=2.8, mean (1998) frequency of health care visits in poor status group=3.9). The home visits agencies in required time for visits was related to and the Kanagawa the treatment and medication that required time and Saitama each client required (mean time for for visits. prefectures, group that required the treatment and Japan. medication=50.2 minutes, mean time for group with no requirement of the treatment and medication=62.7 minutes). There was no relationship between RN experience and home health care experience, the frequency of home visits, and the required time for visits. However, for employment status, part-time nurses (mean=68.1 minutes) spent a significantly longer time per visit than full-time nurses (mean=48.0 minutes) did on home visits.

Table 4 (continued).

Author (Year) Purpose of the Sample and Results study Settings Fujiya, To identify 391 clients The number of visits in terminal care Shimanouchi, frequency of aged 40 and group (mean=4.3) was significantly & Kamei visits, and older at 30 higher than in other groups: medical (1999) direct care VNS and 8 treatment group (mean=2.2), time and home care dementia group (mean=2.0), and life- coordination departments assisted group (mean=2.1). Also, the time in a week of hospitals average time for nursing for four in urban administration per patient in the groups: areas, Japan. terminal care group (mean=79.9 terminal care minutes) was significantly higher than group, medical in other groups: medical treatment treatment group (mean=49.4), dementia group group, (mean=35.0), and life-assisted group dementia (mean=39.9) during one week. group, and physical assistance group (needing help with bathing, etc).

Fujiya (2000) To examine 376 clients Total time for visits during one week relationships aged 65 and was the longest in clients with high between the older at 30 dependence level and severe dementia required time VNS and 8 level (866.0 minutes for one week) for visits and home care than for clients with other levels: low degree of departments dependence level and mild dementia patient’s of hospitals level (245.9), low dependence level dependence in urban and severe dementia level (376.8), and dementia areas, Japan. low dependence level and mild level. dementia level (391.7).

Table 4 (continued).

Author (Year) Purpose of the Sample and Results study Settings Hedtcke, To invest how 260 nurse- The average number of minutes of MacQueen, & home health days at the direct patient care was 224 per day. Carr (1992) nurses spend Visiting The average number of minutes of their time. Nurse documenting that patient care was 87 Association per day. The average number of of Chicago minutes per day for other activities (VNA-C). was 55. The average number of minutes of traveling each day was 106. The average number of visits per day was 4.8—that is productivity (visits/day) for all nurses.

Madigan & To examine 102 home The mean visit time in the home was Fortinsky visits, time, health 51.0 minutes. The highest mean visit (1999) and costs of patients from time (55.1 minutes) was for RNs, resource 10 agencies followed by social worker time (54.3 consumption in Ohio minutes), home care aides (53.7 in the home minutes), and therapy time (45.5 for RNs, minutes). Time for indirect care was therapists, not measured in the study. social workers, and aids in 102 patients.

Ogata, To identify the 32 staff The top three services of largest Kobayashi, total work and nurses of 3 geometric means of intensity (mental Fukuda, Mori, three VNS in effort and physical effort) and time Hashimoto, & dimensions: urban were “Enema/manual removal” (total Otosaka intensity Yokohama, work=84.3; “mental effort”=76.5; (2004) (“mental Japan. “physical effort”=68.7; and effort” and time=15.5), “bed bath”(82.9; 66.0; “physical 66.9; and 15.5, respectively), and effort”) and “assisting with bathing”(79.2; 74.6; time needed 73.8; and 24.1) among 18 nursing for providing services provided by nurses. one nursing Time alone accounted for 39 % of the service. variance in total work, and three dimensions accounted for 96 % of the variance in total work.

Table 4 (continued).

Author (Year) Purpose of the Sample and Results study Settings de Vliegher, To study the 441 home The three most frequently Paquay, interventions nurses in an interventions were “bathing”(n=438), Grypdonck, by nurses organization “clothing”(n=437), and “skin Wouters, in Belgium. care”(n=422). Debaillie, & Geys (2005)

Zimmer & To examine The Home The mean overall time per visit was Groth-Juncker time spent on Healthcare 49.2 minutes. The highest mean per (1983) activities by Team (M.D., visit (69.8 minutes) was for social the physician N.P., S.W.) workers, followed by nurse (M.D.), the of Rochester, practitioners (49.3 minutes), and nurse New York. physicians (39.3 minutes). practitioner (N.P.), and the social worker (S.W.).

Zimmer et al (1983) measured both direct care and indirect care, such as

telephone calls, administration, and travel. Nurse practitioners for home health care spent

35.3 % of the day in direct care, 10.4 % in telephone calls, 31.8 % in administration, and

22.5 % in travel (Zimmer et al., 1983). The proportion of direct care/indirect care is

approximately a 35/65 ratio. On the other hand, according to Hagerty, Chang, and

Spengler (1985), direct care is 53.4 % of a hospital staff nurse’s day. The proportion of

direct care/indirect care is approximately a 50/50 ratio at a hospital.

The two studies that are most relevant to the present study report only direct care

time. Madigan and Fortinsky (1999) analyzed the mean visit time and the mean number

of visits in the home. In the study, time of indirect care was not measured. Also, Adams 47 and colleagues’ studies focused on only direct care (Adams & Michel, 2001; Adams,

Michel et al., 2001).

The number of visits per day is important because reimbursement is on a per-visit basis in Japan. Similarly, it is also important to study the time involved in care in Japan because the LTCI reimburses nursing care depending on the duration of the appointment: less than 30 minutes, from 30 less than 60 minutes, and from 60 less than 90 minutes

(Social Insurance Society, 2000). There are several time studies of visiting nurses in

Japan.

Fukaya, Okabe, and Tukamoto (1998) conducted a time study in Japan during one month and found that the required time for visits was related to the treatment and medication that each client required. Before the LTCI in Japan which started in 2000, the reimbursement per visit was the same, whether the visit was 20 minutes or 90 minutes long. Visits may take more or less time, depending on each client’s condition. Thus, patients who required medications and treatments required longer visits. This finding supports the change in the reimbursement system as introduced by the LTCI.

Fujiya, Shimanouchi, and Kamei (1999) conducted a time study in a week in

Japan. As in the study conducted by Fukaya et al. (1998), the results showed that nurses spent more or less time, depending on the client’s condition. Notably, visiting nurses needed more time for a client with terminal illness, similar to the productivity measures for home care nurses in the US, which recommended less than three visits per day for hospice nurses. In another time study in Japan, Ogata, Kobayashi, Fukuda, Mori,

Hashimoto, and Otosaka (2004) conducted a survey during one week in Japan. This study focused on work intensity and time needed for providing each nursing service for clients, 48

such as enema/manual removal of feces, bed bath, and assisting with bathing. In the

above time studies in Japan, the time study was limited to time spent on clients. These

studies showed that nurses need more time for clients with terminal illness, with higher

dependency levels, and with higher dementia levels. However, it is unclear how visiting

nurses spent their working hours, including nonvisit work that is not for a specific client.

There is no research on concepts of productivity in home-visit nursing care in Japan.

Measuring total hours that visiting nurses work will be important for explaining workload of visiting nurses in Japan. De Vliegher, Paquay, Grypdonck, Wouters, Debaillie, and

Geys (2005) stated that it is difficult for nurses in home health care to explain their

nursing services as a profession to the health policy makers, and there is little research to

support nurses in that debate. In Japan, in the time studies conducted by Fukaya et al.

(1998) and Ogata et al. (2004), only direct care was measured; indirect care was not

measured. There is no research on total/complete workload of visiting nurses.

In support of the procedure for the current study, the time studies by Fujiya et al.

(1999) and Ogata et al. (2004) were conducted over a one week period. The research

shows that visiting nurses were able to record how they spent their time in one week and

that time studies are feasible in Japan.

Gaps in the literature

Most studies in this area report descriptive results with few studies examining the relationships between nurse characteristics and job satisfaction or between productivity and nurse characteristics. The studies that do report on the relationships especially between job satisfaction and nurse characteristics have been equivocal; in some cases 49

there are significant relationships and in other cases there are no relationships. There are

several explanations for the equivocal findings.

First of all, the biggest problem with the research in this area is that instruments

for examining job satisfaction were different. There is little research on job satisfaction in home health care. Although there are many studies of nurse job satisfaction in hospitals, research on job satisfaction has only recently begun to be conducted in home health care settings (Ellenbecker, 2004). Moreover, although the practice environment of home care is different from that of hospitals, there are few studies that demonstrate the traits in home care that attract and retain home care nurses (Flynn, 2003). The four subscales of the NWI-R will be used in the present study. However, several different instruments were used to measure job satisfaction in the studies that were reviewed.

The second biggest problem is that the relationships between nurse characteristics and productivity were not analyzed using the productivity formula for the present study.

There is little research on the productivity of home care nurses. Calculating productivity in home health care is customarily as simple as calculating visits per day, and visits per day was presently only with descriptive information in the articles. The research on productivity of home care nurses in the U.S. is very dated and there is nothing more recent. In addition, there was no research on the relationships between nurse characteristics and productivity that could be used for the present study.

Third, the samples in almost all studies in this area were not collected randomly.

A convenience sampling approach was used instead, so the results may not be generalizable to the population of all home healthcare nurses. 50

Despite the equivocal nature of the findings in this area, nurse characteristics,

such as years of experience and employment status, may be important variables. Because

the study is being undertaken in Japan, it is important to include these characteristics to

allow for a more comprehensive understanding of Japanese home health care.

Age and years of experience have most consistently been shown to influence

intent to stay and retention (Ellenbecker, 2004). The age of nurses may affect job

satisfaction because older and younger generations differed only slightly in regard to

values, such as job satisfaction, although younger nurses valued economic return more

than older nurses in a hospital (McNeese-Smith & Crook, 2003). Moreover, the number

of years of experience is positively related to staff retention in hospitals of the U.S.

(Leveck & Jones, 1996). It may be important to examine whether nurse characteristics,

such as age and years of experience, are related to job satisfaction in Japan. For the

present study, gender will be only descriptive information because almost all nurses in

Japan are female.

There was little research on the relationships between productivity and nurse

characteristics. However, Fukaya et al. (1988) found part-time home health care nurses

spent a significantly longer time per visit (mean=68.1 minutes) than full-time nurses did

on home visits (mean=48.0 minutes). Employment status may be associated with

productivity, using the defined formula of productivity in the present study.

There was no research on the relationships between productivity and job

satisfaction among home health care nurses. Only descriptive information was shown in

most studies in productivity. However, the research on relationships between productivity and job satisfaction among home care nurses may be important. Ellenbecker (2001) 51

suggests further research is needed on the variables related to job satisfaction. In the same

way, research on the relationship between job satisfaction and professional autonomy and

the relationship between productivity and quality of care for patients are important

(Ellenbecker, 2001). Job satisfaction has a positive effect on quality of care (Navaie-

Waliser et al., 2004). Thus, research on the relationship between productivity and job

satisfaction will be important in the future. Workload demands may influence the level of

satisfaction. These gaps will be significantly addressed by research on productivity

among visiting nurses, using the defined formula of productivity in the present study.

CHAPTER III

Methodology

The purpose of the study was to identify factors related to job satisfaction among visiting nurses in Japan. The relationships between structure (nurse characteristics) and outcome (job satisfaction), between structure and process (productivity), and between process and outcome will be examined. The chapter begins with the research design of the present study. Next, the chapter presents the study setting, sample, and sample size calculation. The study procedures for data collection and measurements are described.

The chapter ends with the protection of human subjects.

Design

The present study used a descriptive correlational design. Researchers use

correlational research when they investigate relationships between variables identified in

theories or in practice (Burns & Grove, 2005). Previous studies in this area of

investigation have used descriptive or descriptive correlational designs as seen in Table 5.

Table 5

A summary of the relevant research: Research design

Author Design Sampling Sample (% response Access (Year) rate) Anthony & A descriptive Not provided 529 home care nurses Not sure. Milone- study in Connecticut. Nuzzo (2005)

Armstrong- A descriptive A random 1044 community health A survey was Stassen, & study sample nurses in public health, mailed. Cameron selected from home care, and (2005) the College of community care access Nurses of center (CCAC) Ontario. agencies of 1524 completed questionnaire (52% response rate) in Ontario, Canada.

Elder, A descriptive A 57 employees (20% A survey was Wollin, study. convenience response rate) as mailed. Hartel, sample. registered nurses and Spencer, & personal carers in Sanderson residential (n=20) and (2003) community (n=37) healthcare settings in Brisbane, Queensland, Australia.

Ellenbecker A descriptive A 254 nurses (40% A survey was (2001) correlational convenience response rate) from 4 placed in study sample. home health agencies staff in the northeast, mailboxes. southwest, and western United States.

Table 5 (Continued).

Author Design Sampling Sample (% response Access (Year) rate) Ellenbecker A descriptive A 340 home healthcare A survey was & Byleckie study convenience nurses (38% response delivered by (2005a) sample. rate) from 11 agencies a researcher in Maryland, Virginia, at staff Michigan, Tennessee, meetings, or Oregon, and the a survey was District of Columbia. posted in nurses’ mailboxes.

Ellenbecker A descriptive A 340 home health care A survey was & Byleckie correlational convenience nurses (38% response delivered by (2005b) study sample. rate) from 10 home a researcher care agencies. when staff had meetings, or the survey was placed in nurses’ mailboxes.

Flynn (2003) A descriptive A random 403 home care nurses A survey was study sample from (61% response rate) in mailed. mailing lists 48 states. from the (Nationwide study American randomly) Nurses Association and the American Nurses Credentialing Center.

Flynn (2005) A descriptive A random 403 home care nurses A survey was study sample of (61% response rate) in mailed. home care the U.S. nurses selected from mailing lists.

Table 5 (Continued).

Author Design Sampling Sample (% response Access (Year) rate) Flynn, A descriptive A random 403 home care nurses A survey was Carryer, & study sample of (61% response rate) in mailed. Budge (2005) home care the U.S. and 320 nurses district nurse (50% selected from response rate) in New mailing lists Zealand, and 669 in the U.S. hospital-based nurses A pooled existing convenience secondary data in the sample in U.S. New Zealand. A sample of hospital-based nurses from a secondary data in the U.S.

Lynch (1994) A descriptive A 66 home health nurses A survey was study convenience (65% response rate) distributed in sample. from 3 agencies (two in mailboxes. Pennsylvania and one in New Jersey).

Moore & A descriptive A 67 home health nurses A survey was Katz (1996) correlational convenience from 3 agencies in the placed in study. sample. Midwest and 71 acute mailboxes at care surgical nurses 1 agency, and from a prior study. a survey was distributed by the researchers at their monthly staff meetings at 2 agencies.

Table 5 (Continued).

Author Design Sampling Sample (% response Access (Year) rate) Navaie- A descriptive A 188 home health staff A survey was Waliser, correlational convenience (55% response rate) at mailed. Lincoln, study sample. an agency, including 52 Karuturi, & nurses (RNs and Reisch LPNs). (2004)

Smith-Stoner A descriptive Not sure. 841 home care nurses Notices were (2004) study from online survey. posted on the Web by the National Association for Home Care and many individual state home care associations, or notices were sent via electronic mail.

Tullai- A descriptive A 82 staff RNs of 11 A survey was McGuinness, correlational convenience home health care posted in the Madigan, & study sample. agencies in Ohio. RNs’ office Anthony mailboxes. (2005)

The advantage of a descriptive correlational design is that the researcher can

explore the relationship between not only two but also more variables within a currently

occurring situation (Burn et al., 2005). A descriptive correlational design facilitates the

understanding of many interrelationships that exist in a situation in a short time, so 57

variables in the study must be clearly described to be understood without confusion (Burn et al., 2005).

The disadvantage of a descriptive correlational design is that there is a lack of manipulative control over the independent variables (Polit & Hungler, 1999). Thus, the type of design is not to determine cause and effect, but to explain the nature of relationships (Burns et al., 2005). However, hypotheses may be generated from the results of correlational research and the hypotheses could guide future experimental studies examining cause and effect (Burns, et al., 2005).

Setting and Sample

The present study was conducted in Japan. The setting of the study was VNSs located in a prefecture in Japan. The inclusion criteria were visiting nurses, including both part-time nurses and full-time nurses, who were currently working at participating

VNSs in Japan.

The exclusion criteria included nurses who were in management positions. Top managers work in a management position part of the time and the rest of the time as visiting nurses. Because the focus was the time spent by visiting nurses, including managers would interfere with the understanding of the time spent by nurses in direct and indirect care. Thus, the exclusion criteria were visiting nurses working as top managers at

VNSs.

A convenience sample of visiting nurses was obtained from participating VNSs,

Japan. One advantage of a convenience sample is that it is inexpensive and accessible

(Burns et al., 2005). The disadvantage of a convenience sample is that the results may not be generalizable to the population of all visiting nurses in Japan. However, convenience 58 sampling is useful for correlational studies in new areas while the method is not recommended for research on the impact of a treatment (Burns et al., 2005). As shown in

Table 5, most researchers in this area use a convenience sample in their studies.

Correlation research may involve either nonrandom or random sampling methods (Burns et al., 1995). A convenience sample, despite its limitations, may be useful and provide new information in this under-developed area of research.

Sample Size and Power Analysis

In the present study, visiting nurses who were currently working in participating

VNSs in Japan were obtained through those VNSs. It was impossible for one investigator to obtain a sample from all of Japan due to limitations of time and money. Thus, it is important to evaluate the adequacy of the sample size in order to obtain a sample that would reflect the population and to find comparisons and significance (Burns & Grove,

1995). Power analysis involves the relationships among the four variables: sample size

(N), power, effect size (ES), and significance criterion (alpha) (Cohen, 1988) and is used to calculate subjects needed in the present study. Thus, power, effect size, and significance criterion will be needed to estimate an appropriate sample size.

According to Burns and Grove (2005), “Power is the capacity of the study to detect differences or relationships that actually exist in the population”(p.344). In other words, “power is the capacity to correctly reject a null hypothesis” (Burns et al., 2005, p.344). Cohen (1988) suggests that a power of .80 is sufficient because a value smaller than .80 has too great risk of a Type II error. However, power of .80 might be too big a

Type II error rate for a study that has not been done before in Japan. Thus, power was set at .85 in the present study. 59

Effect size is “the degree to which the phenomenon is present in the population or the degree to which the null hypothesis is false” (Cohen, 1988, p.9). Effect size is calculated from previous studies. A large effect size (r=.50) was found in the research on

the relationship between productivity and nurse characteristics (Feldman et al., 1988).

Tullai-McGuinness (2003) conducted research on relationships between nurse

characteristics and autonomy, using a medium effect size of .30. The actual correlation

between nurse characteristic (certification) and control over practice decisions was r=-27

(p<.01). Correlation from research by Moore et al. (1996) ranged from -.36 to .56. In the summary, the effect sizes from past studies range between medium (.30) or large (.50).

The statistical test to be used is multiple regression. Thus, a medium effect size of .15 for multiple regression (Cohen, 1992) was set for the present study.

Significance criterion (alpha) is the “probability of making a type I error” (Gordis,

2004, p.133). The alpha is called p value (Gordis, 2004). For this study, the alpha was set at the .05 level because the level had been suggested for use in most studies of behavioral science research (Cohen, 1988).

To determine sufficient sample size G*Power 3 (Faul, Erdfelder, Lang, &

Buchner, in press) was used. The number of independent variables was four (age, employment status, experience years, and productivity) for multiple regression. Using the following information: power (.85), medium ES (.15), and alpha (.05), a sample size of

95 was required.

Data Collection Procedure

First, the study was approved by the Institutional Review Board of the Case

Western Reserve University after getting a letter of cooperation from a top manager from 60

at least one VNS in Japan. Then, the investigator contacted top managers of VNSs in a

prefecture in Japan by mail and phone in order to obtain permission to distribute a survey

to visiting nurses currently working in VNSs. Next, the investigator delivered a survey to

visiting nurses at a staff meeting or in person, or posted the surveys in nurses’ mailboxes.

There were two instruments in the survey: the nurse workload form (Appendix A)

and the nurse questionnaire (Appendix B). First, nurses completed the nurse

questionnaire (Appendix B) because if they completed the NWI-R after they tracked

workload, it could have influenced their results. Then nurses wrote their workload

everyday for one week on the nurse workload form (Appendix A).

Measurements

The nurse workload form (Appendix A) included the number of visits (direct

care) and types of visits (direct care), hours (direct care and indirect care), and types of

services (direct and indirect). Productivity was calculated by the researcher after data

collection was completed. The nurse questionnaire (Appendix B) included nurse

characteristics, overall job satisfaction, and the NWI-R.

NWI-R

The Nursing Work Index-Revised (NWI-R) was developed for measuring aspects of nurses’ practice environment (Aiken & Patrician, 2000). The instrument is suitable for measuring nurse job satisfaction because the work environment contributes to nurse job satisfaction. Job satisfaction is often measured to assess the quality of the work environment (Ellenbecker, 2001).

The NWI-R has been utilized in acute care settings, but recently the instrument has also been used in home health settings in the U.S. The following studies examined 61 whether this is an appropriate use of the NWI-R. Initially, Flynn and Deatrick (2003) pointed out that there were no studies in home care settings to identify attributes that are important to the support of their practice, and they conducted seven focus-groups with 58 nurse participants in the Mid-Atlantic region of the U.S. before deciding to use the NWI-

R in home care settings. The researchers concluded that the attributes of home care settings were similar to those described in both hospital settings and the magnet hospital, and that the NWI-R is an appropriate tool for home health settings. Their findings offer guidance for developing workplace environments in home care settings to support nurses’ professional practice (Flynn, et al., 2003).

Later, Flynn, Carryer, and Budge (2005) conducted a study to determine whether hospital-based, home-care, and district nurses identified the same core set of organizational attributes that are important to the support of professional practice. The three samples included 403 home care nurses in the United States, 320 district nurses in

New Zealand and 669 hospital-based nurses in the U.S. Approximately 80 percent of the nurses agreed or strongly agreed with 47 of the 49 items on the NWI-R. However, mean scores (170.61) among home health care nurses in the U.S. were significantly lower as compared with the other two groups: district nurses (175.90) and U.S.hospital nurses

(176.44). The researchers suggested that further research in home care settings is needed to determine how to support nurses’ professional practice.

Flynn (2005) states that characteristics of the work environment contribute to nurses’ job satisfaction and suggests that managers should develop strategies to improve nurse retention in home care settings, emphasizing the work environment. Moreover, the

NWI-R was used in a recent study of a sample of 82 nurses from 11 home health care 62

agencies in Ohio on autonomous home care practice. Two subscales from the NWI-R,

“the autonomy” and “the control over the practice setting” were used for the home care

settings (Tullai-McGuinness et al., 2005). Tullai-McGuinness, Madigan, and Anthony

(2005) used three instruments (Participation in Decision Activities Questionnaire

[PDAQ], NWI-R, and Global Appraisal of Autonomous Practice [GAP]) to measure how much autonomous practice is exercised in home health care. Overall, RNs perceived more clinical autonomy (control over practice decisions; mean=3.32) than organizational autonomy (control over practice setting decisions; mean=3.02), using the NWI-R

(possible range, 1-4).

Thus, the NWI-R subscales of autonomy and control over nursing practice are identified as important organizational attributes in the home health settings. Also, the other two subscales in the NWI-R, “nurse-physician relationship” and “organizational

support,” are important for job satisfaction. Ellenbecker and Byleckie’s (2005a, 2005b) survey confirms that the “relationship with physician” and “organizational components”

as well as autonomy are important for job satisfaction. Thus, all four subscales of the

NWI-R were used to measure job satisfaction in the present study.

In Japan, Kanai (2005) used the NWI-R to compare nurses in the U.S. and in

Japan, and presented the results of the survey in a health research forum at the Pfizer

Health Research Foundation 2005. There is no published article on the findings. The

other study on the NWI-R in Japan was conducted by Kobayashi, Suzuki, Sakaguti, Mitty,

Norman, and Mezey (2006) in order to establish the reliability and validity of the NWI-R

(Aiken & Patrician, 2000) in Japan. Based on their findings, the NWI-R is considered

appropriate to use for measuring job satisfaction in health care in Japan. Thus, the NWI-R 63

can be used in VNS settings in Japan, in order to identify organizational attributes that

visiting nurses think are important to the support of their practice. The instrument may be

useful to identify how visiting nurses consider their practice in Japan. The result of the

study suggests strategies to attract and retain visiting nurses in Japan. For the NWI-R

scoring, consistent with past research, higher values indicate greater satisfaction.

A single item indicator for job satisfaction will be used as well. Using a visual

analog scale, a 100 mm line, nurses will be asked to mark their job satisfaction. The

anchors on either end are “not at all” and “very much.” This provides a continuous

measurement to solve the difficulty of obtaining fine values (Burn, et al, 2005) and has been used in past research (Tullai-McGuinness, 2003).

Reliability and Validity

The NWI-R was developed by Aiken and Patrician (2000) based on the NWI by

Kramer and Hofner (1989). The NWI-R has good reported reliability. Aiken and colleagues report a Cronbach’s alpha of 0.96 for the entire NWI-R. The alphas of each subscale were 0.75 for autonomy, 0.79 for control, and 0.76 for nurse-physician relationships (Aiken et al., 2000). Validity, including content validity and criterion validity, was established as follows: Three original researchers of the magnet hospitals affirmed the content validity in capturing elements of professional practice models

(Kramer & Hofner, 1989). Criterion-related validity was evidenced by the fact that higher

NWI-R subscale scores were found in magnet hospital (Aiken, Smith, & Lake, 1994) and in dedicated AIDS units (Aiken & Sloane, 1997).

The present study was conducted in Japan, using the NWI-R (Aiken et al., 2000).

Kobayashi et al. (2006) translated the NWI-R into Japan and provided evidence of 64

reliability and validity. Reliability of the NWI-R in Japanese was assessed by using the

Cronbach’s alpha for the scale with an alpha of 0.96. The NWI-R had strong reported

content validity with a content validity index (CVI) score of .95 to .97. Criterion-related

validity was assessed by the job satisfaction scale (Yamashita, 1995). There was a strong correlation (r = -.65, p <.01) between total scores of the NWI-R (Aiken et al., 2000) and

the job satisfaction (Yamashita, 1995) for occupational satisfaction of hospital nurses that

consist of 25 item questions with a 5-point Likert scale.

The NWI-R was translated into Japanese as the following. First, two experts

independently translated the NWI-R into Japanese. Then, the two experts discussed each

translation and came to consensus on the Japanese version. Next, two translators

independently translated it into English. Two researchers discussed each translation and

came to consensus on the English version. Finally, two researchers who are familiar with

the NWI-R checked whether there were any differences between the original NWI-R and

the NWI-R translated into Japanese.

In the present study, the sample was visiting nurses at VNSs. Before the survey

was conducted with visiting nurses, an investigator who worked as a visiting nurse

checked whether visiting nurses could understand the words in the Japanese NWI-R. Two

words needed to be replaced because the settings were VNSs in the present study. The

meaning is the same, but the word is different. “Shicho” is used in a hospital in Japan, but

“shocho” is used in VNSs. Also, “byoto” is used in a hospital, but “sutaisyon” is used in

VNSs. Thus, it will be noticed that the word “shicho” is replaced with “shocho” and that

the word “byoto” is replaced with “sutaisyon” when visiting nurses answer questions in

the the NWI-R of the present study. When Tullai-McGuinness (2003) conducted survey 65 among home healthcare nurses using the NWI-R, one word was replaced with different word: “the word unit was replaced with team” (p.67) without confusion.

In the present study, reliability of the NWI-R was assessed by using the

Cronbach’s alpha for the scale. Validity was assessed by correlation between the NWI-R and the question on overall job satisfaction. “Successive verification of validity” is obtained through repeated use of the measurement (Burns et al., 1995). The NWI-R has been used twice in Japan. After the development of a measurement, other researchers begin using the measurement (Burns et al., 2005) and contribute to the evidence of validity of the measure. Thus, the present study will contribute evidence on the validity of the NWI-R in Japan.

Statistical analysis

Variables that include a measurement of the NWI-R (Aiken, 2000) are shown in

Appendix C. All data was collected from the nurse workload form (Appendix A) and the nurse questionnaire (Appendix B). The collected data was transferred to SPSS statistical software for subsequent analysis of research questions using the codebook (See Appendix

C). Blank or invalid data was transferred as missing data in SPSS.

Descriptive statistics and measures of central tendency and dispersion were used to examine the data prior to analysis. Also, the statistical assumptions for multiple regression and correlation were examined, including multicollinearity, outliers, and influential data points.

Research questions

There were five research questions in the present study:

Research Question 1: Is “structure” associated with “outcome”?

- Are nurse characteristics associated with job satisfaction?

The independent variables were age, employment status, and years of

experience. The dependent variable was the total score of the NWI-R.

Multiple regression will be used for research question 1. Then a second

analysis was used the same independent variables with the dependent

variable of the single item indicator, overall job satisfaction.

Research Question 2: What is the productivity of Japanese visiting nurses?

Productivity was included as descriptive data. The productivity was calculated

using the formula as previously stated:

Total hours (direct* and indirect**)÷Total number of visits (direct)=Hours

per visit

Total hours (direct and indirect)÷working days÷Hours per visit= Visits per

day

*direct care hours = hours spent by visiting nurses in the patient’s home

**indirect care hours= the total number of hours worked excluding direct

care

Research Question 3: Is “structure” associated with “process”?

- Are nurse characteristics associated with home-visit nursing care productivity?

The independent variables were age, employment status, and years of

experience. The dependent variable was productivity. Multiple regression

was used for research question 3. 67

Research Question 4: Is “process” associated with “outcome”?

- Is home-visit nursing care productivity associated with job satisfaction?

The independent variable was productivity. The dependent variable was

the total score of the NWI-R. Pearson’s correlation was used for research

question 4. A second correlation included the relationship between

productivity and the single item indicator, overall job satisfaction.

Research Question 5: Which structure and process variables are most important in explaining job satisfaction?

The independent variables were age, employment status, years of

experience, and productivity. The dependent variable was the total score

of the NWI-R. Multiple regression was used for research question 5. Then

a second analysis used the same independent variables with the dependent

variable of the single item indicator, overall job satisfaction.

As previously stated, most nurses in Japan were assumed to be female, so gender was included as only descriptive data. Also as previously stated, job satisfaction was measured by the NWI-R and the overall job satisfaction.

Protection of Human Subjects

The present study involved human subjects using the data from the information in the questionnaires written by visiting nurses. To protect human subjects, the present study was approved by the Institutional Review Board (IRB) of Case Western Reserve

University.

Participants were informed that confidentiality of information would be maintained, and that they could withdraw from the study at any time without penalty. The 68 subjects were also notified that the VNSs would not receive individual results. The privacy of the results was protected with no name on the questionnaires. The results were not analyzed for each VNS, but for all of participating VNSs.

Chapter IV

Results

This chapter reports the results of the study to answer research questions. The

purpose of this study was to identify productivity in home-visit nursing care in Japan and

to examine relationships between nurse characteristics, productivity, and job satisfaction.

Recruitment

The investigator contacted top managers of 46 Visiting Nurse Stations (VNSs) in

Japan by mail and phone or in person in order to obtain permission to distribute a survey

to visiting nurses currently working in the VNSs in an urban prefecture. Twenty eight

VNSs agreed to participate. The investigator obtained a letter of cooperation from the top

managers from 28 participating VNSs. Next, the investigator delivered the survey to 137

visiting nurses at a staff meeting or in person, or posted the survey in nurses’ mailboxes.

Finally, using a modified Dillman approach (1978), a reminder letter was sent to all the

VNSs from which the investigator had the cooperation letters to encourage the nurses

who had not done so to return the surveys. From the 28 VNSs, 100 of 137 nurse surveys

were returned for a response rate of 73.0 %.

Data were not collected by VNS to reduce the risk of breach of confidentiality. In

other words, which nurses from each VNS were not tracked. Unlike American home care

agencies, Japanese VNSs do not differ in ownership or structure (i.e. for-profit or non-

profit). Thus, there were no data available on the average response rate by VNS. All the

VNSs were located in one urban prefecture. 70

Sample Description

Nurses in this study were on average 40.4 years (SD = 8.4) of age (Table 6).

There were 97 (97%) RNs and 3 (3%) LPNs (Table 8). There were 72 nurses who started

their careers as RNs. For the nurses who started their careers as RNs, nurses had, on

average, 12.7 (SD = 6.2) years of the experience as a nurse and, on average, 4.4 years (SD

= 3.4) of experience in home care. There were 26 nurses who started their careers as

LPNs and 3 who were still LPNs. For the nurses who started their careers as LPNs,

nurses had, on average, 15.2 years (SD = 9.5) of experience as RNs and, on average, 5.3 years (SD = 5.9) experience in home care as RNs.

Table 7 shows nurses’ age distribution. Nurses had, on average, 14.8 years (SD =

7.7) of experience as a nurse (Table 6), 13.4 years (SD = 7.2) of experience as a RN and

1.4 years (SD = 4.5) of experience as a LPN in any settings; on average 4.7 years (SD =

4.2) of experience as a RN & 0.1 years (SD = 0.6) of experience as a LPN in home health care (HHC); and on average 3.3 years (SD = 3.1) of experience as a RN & 0.04 years (SD

= 0.3) of experience as a LPN at the current visiting nurse station (VNS).

Almost all nurses were female (98.0%, n=98). More than half (60.2%, n=59) worked full-time, and the remainder worked part-time. While almost all nurses’ current licenses were as Registered Nurses (97.0%, n=97), more than one-fourth (26.5%, n=26) started their nursing careers as Licensed Practical Nurses, the remainder started as

Registered Nurses (73.5%, n=72). The majority of nurses (82.0%, n=82) graduated from a diploma program. Only 3 (3%) had a baccalaureate degree. None had a graduate degree.

Table 8 provides detailed description of the nurse education characteristics.

Table 6

Sample Characteristics: Age and Years of Experience

Characteristic Mean (SD) Median Range

(yrs) (yrs) (yrs)

Age (n=99) 40.4 (8.4) 40.0 26 – 62

Experience as a nurse (RN & LPN) (n=96) 14.8 (7.7) 13.5 2.3–35.0

-Experience as a RN (n=97) 13.4 (7.2) 12.5 0.0–30.2

-Experience as a LPN (n=98) 1.4 (4.5) 0.0 0.0–33.0

-HHC Experience as a RN (n=96) 4.7 (4.2) 3.6 0.0–19.0

-HHC Experience as a LPN (n=97) 0.1 (0.6) 0.0 0.0–5.0

-Current VNS Experience as a RN (n=98) 3.3 (3.1) 2.0 0.0–15.0

-Current VNS Experience as a LPN (n=97) 0.04 (0.3) 0.0 0.0–3.2

For those beginning as RNs (n=72)

-Experience as a RN (n=70) 12.7 (6.2) 12.1 2.3–30.2

-Experience in home care as a RN (n=70) 4.4 (3.4) 3.5 0.3–15.0

For those beginning as LPNs (n=26)

-Experience as a nurse (RN & LPN) (n=26) 20.6 (8.5) 19.3 5.1–35.0

-Experience as a RN (n=26) 15.2 (9.5) 15.3 0.0–29.0

-Experience in home care as a RN (n=25) 5.3 (5.9) 4.0 0.0–19.0

Table 7

Age Distribution

Age in years (n=99) Frequency Valid Percent Cumulative Percent

25-29 10 10.0 10.1

30-34 15 15.0 25.3

35-39 22 22.3 47.5

40-44 25 25.3 72.7

45-49 14 14.0 86.9

50-54 4 4.0 90.9

55-59 7 7.0 98.0

60-64 2 2.0 100.0

Table 8

Sample Characteristics: Gender, Employment status, and Education

Characteristics % n

Gender (n=100)

Female 98.0 98

Male 2.0 2

Employment Status (n=98)

Full Time 60.2 59

Part Time 39.8 39

Current License (n=100)

Registered Nurse (RN) 97.0 97

Licensed Practical Nurse (LPN) 3.0 3

Starting Career (n=98)

Registered Nurse (RN) 73.5 72

Licensed Practical Nurse (LPN) 26.5 26

Highest education (n=100)

Licensed practical nurse courses (LPN) 3.0 3

Nursing School (Diploma program) 82.0 82

Junior College (Associate degree) 12.0 12

University / College (Baccalaureate degree) 3.0 3

Master’s course (Master degree) 0.0 0

Doctoral Course (Doctoral degree) 0.0 0

Job Satisfaction

There were two scales of job satisfaction used in the survey. The first instrument was a single item indicator for the overall job satisfaction. Using a visual analog scale, a

100 mm line, nurses were asked to mark their job satisfaction. The average job satisfaction rating was 62.5 (SD = 20.5). Figure 2 provides a histogram of the overall job satisfaction scores.

The NWI-R was used as the second measure of satisfaction. There were 15 items of this version of the NWI-R. The NWI-R total mean was 40.8 among visiting nurses in

Japan (Table9). Subscales were scored as follows: autonomy (total mean =15.1), control

(total mean=18.2), physician relationships (total mean=7.8), and organizational support

(total mean=28.3).

10 Frequency

0 0.0 20.0 40.0 60.0 80.0 100.0

Figure 2. Histogram of the overall job satisfaction scores

Table 9

Job Satisfaction (The NWI-R and the overall job satisfaction)

Job Satisfaction Mean (SD) Median Actual Possible

range range

The VAS overall job satisfaction (N=100) 62.5 (20.5) 65.8 0 – 100 0–100

The NWI-R (N=92) 40.8 (6.1) 41.0 20–54 15–60

Autonomy subscale (N=95) 15.1 (2.6) 15.0 7–20 5–20

Control over the practice setting subscale (N=98) 18.2 (3.2) 18.0 9–26 7–28

Nurse physician relationship subscale (N=97) 7.8 (1.7) 8.0 3–12 3–12 Organizational support subscale (N=94) 28.3 (4.0) 28.0 15–37 10–40

Reliability and Validity

The NWI-R

Reliability and validity of the NWI-R in the present study are for the following.

Reliability. In the present study, reliability of the NWI-R was assessed by using the Cronbach’s alpha for the overall scale with an alpha of 0.82. The alphas of each subscale were 0.75 for autonomy, 0.62 for control, 0.79 for nurse-physician relationships, and 0.73 for organizational support.

Validity. Validity was assessed by correlation between the NWI-R and the question on overall job satisfaction with r=0.47 (p<.001), indicating that there is a moderate and significant relationship between the two instruments.

Analyses to Answer Research Questions

Before answering the research questions, the required assumptions for multiple regression were evaluated.

Testing Assumption of Multiple Regression

The assumptions for multiple regression were evaluated. These assumptions included the four primary residual assumptions, multicollinearity, and influential data points. All of the following assumptions were met except for the homoscedasticity for which the results were not homoscedastic. However, this assumption can be violated without affecting the stability of the results.

Four primary residual assumptions. The first assumption was whether the mean of standardized residual is zero, which was met. Second, the assumption of normality of the distribution was examined by graphical devices, such as a P-P plot (that shows lines of observed and expected residuals) and a histogram. Both assumptions were met. Third, 78

the assumption of homoscedasticity was examined by a bivariate scatterplot. Fourth, the

Durbin-Watson statistic, a measure of autocorrelation of errors, was used to assess the

assumption. The Durbin-Watson was approximately 2, meeting the assumption.

Multicollinearity. The presence of multicollinearity was evaluated by tolerance

and the variance inflation factor (VIF). There were no multicollinear variables; the largest

VIF was less than 2.7.

Influential data points. Influence, a product of leverage and discrepancy, was

measured by Cook’s distance.

Research Question 1

Research questions 1 is: Is “structure” associated with “outcome”? -Are nurse

characteristics (age, employment status, and years of experience) associated with job

satisfaction?

The bivariate correlations of nurse characteristics and each measure of job

satisfaction were shown in the tables 10 and 11. Table 10 describes the correlations of

nurse characteristics with job satisfaction (the NWI-R). The relation between

employment status and job satisfaction (the NWI-R) was non-significant (r=.114; ns).

Table 11 describes correlation of nurse characteristics with overall job satisfaction.

There were no significant correlations.

Next, multiple regression was used for variables predicting job satisfaction of the

NWI-R (Table12) to answer the research question 1. The three independent variables did not explain a significant amount of variance (Adjusted R2=-.005; F=.85; p=.47). Then multiple regression was used for variables predicting job satisfaction of the single item 79 indicator, overall job satisfaction (Table13). The three independent variables did not explain a significant amount of variance (Adjusted R2=-.025; F=.23; p=.88).

Table10

Correlation of nurse characteristics with job satisfaction (the NWI-R)

The NWIR Age Employment Experience

NWIR 1.000 -.003 .114 .063

Age 1.000 .067 .787***

Employment 1.000 -.053

Experience 1.000

Note. *p<.05; **p<.01; ***p<.001

Table11

Correlation of nurse characteristics with job satisfaction (the overall job satisfaction)

Satisfied Age Employment Experience

Satisfied 1.000 .015 -.067 .050

Age 1.000 .067 .787***

Employment 1.000 -.053

Experience 1.000

Note. *p<.05; **p<.01; ***p<.001

Table 12

Regression analysis for three variables predicting job satisfaction (the NWI-R)

Unstandardized Unstandardized Standardized Coefficients Coefficients Coefficients B Std. Error Beta Age -.129 .129 -.177

Employment Status 1.700 1.355 .137

Years of Experiences .166 .140 .209

Note. Dependent variable: total score NWI-R. F =.847. Adjusted R2=-.005

Table 13

Regression analysis for three variables predicting job satisfaction (the overall job satisfaction)

Unstandardized Unstandardized Standardized Coefficients Coefficients Coefficients B Std. Error Beta Age -.114 .420 -.047

Employment Status -2.484 4.426 -.060

Years of Experiences .223 .458 .084

Note. Dependent variable: Satisfied with current job. F =.229. Adjusted R2=-.025

Research Question 2

Research questions 2 is: What is the productivity of Japanese visiting nurses?

Productivity was calculated using the formula:

Total hours (direct* and indirect**)÷Total number of visits (direct)=Hours

per visit

Total hours (direct and indirect)÷working days÷Hours per visit= Visits per

day

*direct care hours = hours spent by visiting nurses in the patient’s home

**indirect care hours= the total number of hours worked excluding direct

care

In the present study, productivity was on average 3.76 (SD=1.05) visits/day

(Table 17). Tables 14 through 16 provide detailed description of workload in Japan. Both direct care and indirect care, such as travel, documentation, and telephone, were measured. Visiting nurses spent average 1018 (SD=454) minutes for one week in direct care and average 766 (SD=407) minutes for one week in indirect care (Table 16). Direct care is 57.8% of a visiting nurse’s week. The proportion of direct care / indirect care ratio is approximately a 58/42 ratio at a visiting nurse station in Japan. The percentage for the amount of indirect care time spent on each activity is the following: travel (41.5 %), documentation (20.2 %), telephone (4.5 %), meeting (14.4 %), preparation (8.0 %), and others (11.4 %).

Table 14

Workload (total hours, visits number, and working days)

Mean (SD) Median Range

Total hours (direct & indirect) for 1 week (N=99) 29.8 (12.7) 29.4 1.6-56.7

Total number of visits (direct) for 1 week (N=100) 17.1 (7.5) 17.0 1-36

Total working days for 1 week (N=100) 4.49 (1.36) 5.0 1-7

Note. 18 nurses worked more than 5 days.

Table 15

Workload (Type of visits)

Mean (SD) Median Range

(visits) (visits) (visits)

LTCI 1 for 1 week (N=100) 2.21 (2.17) 2.0 0-11

LTCI 2 for 1 week (N=100) 9.67 (4.84) 10.0 0-20

LTCI 3 for 1 week (N=100) 0.73 (1.09) 0.0 0-5

Medical insurance for 1 week (N=100) 4.34 (3.42) 4.0 0-14

Private payment for 1 week (N=100) 0.06 (0.31) 0.0 0-2

Others for 1 week (N=100) 0.11 (0.35) 0.0 0-2

Note. LTCI=Long-Term Care Insurance

Table 16

Workload (care time minutes)

Mean (SD) Median Range

(minutes) (minutes) (minutes)

Total time minutes for 1week (N=99) 1789 (763) 1765 95-3400

Total direct care time for 1 week (N=99) 1018 (454) 1010 60-2205

Total indirect care time for 1 week (N=100) 766 (407) 722 35-1830

-Travel time for 1 week (N=100) 296 (161) 278 20-740

-Documentation time for 1 week (N=100) 151 (103) 120 0-490

-Telephone time for 1 week (N=100) 37 (40) 29 0-230

-Meetings time for 1 week (N=100) 115 (106) 88 0-550

-Preparation time for 1 week (N=100) 57 (37) 50 0-210

-Others for 1 week (N=100) 110 (158) 43 0-780

Table 17

Productivity (Visits per day)

Mean (SD) Median Range

Productivity (N=99) 3.76 (1.05) 3.80 1.0-6.4

=Visits per day

=Total hours (direct* and indirect**)÷working days÷Hours per visit

Hours per visit (N=99) 1.77 (0.45) 1.72 1.12-4.63

= Total hours (direct* and indirect**)÷Total

number of visits (direct)

Note. *direct care hours = hours spent by visiting nurses in the patient’s home

**indirect care hours= the total number of hours worked excluding direct care

Research Question 3

Research questions 3 is: Is “structure” associated with “process”? -Are nurse

characteristics associated with home-visit nursing care productivity?

Table 18 describes the correlation between nurse characteristics with productivity.

There is a weak, negative correlation (r=-.24; p=.008) of employment status with productivity such that those who worked more hours had more productivity.

Multiple regression was used for variables (age, employment status, and years of experiences) predicting productivity (Table19). The three independent variables did not explain a significant amount of variance (Adjusted R2=.030; F=1.96; p=.13).

Table 18

Correlation of nurse characteristics with productivity

Productivity Age Employment Experience

Productivity 1.000 .010 -.24** .055

Age 1.000 .067 .787***

Employment 1.000 -.053

Experience 1.000

Note. *p<.05; **p<.01; ***p<.001

Table 19

Regression Analysis for Variables predicting productivity

Unstandardized Unstandardized Standardized Coefficients Coefficients Coefficients B Std. Error Beta Age -.002 .021 -.018

Employment Status -.510 .221 -.239*

Years of Experiences .008 .023 .056

Note. Dependent variable: productivity. F=1.96. Adjusted R2=.030; R2=.061

*p<.05; **p<.01; ***p<.001

Research Question 4

Research questions 4 is: Is “process” associated with “outcome”? -Is home-visit nursing care productivity associated with job satisfaction?

Pearson’s correlation was used for research question 4. First, correlation between productivity and the NWI-R scores was done. There was a weak, negative correlation

(r=-.19; p=.03) between productivity with the NWI-R. A second correlation included the relationship between productivity and the single item indicator, overall job satisfaction and there was no significant correlation (r=-.027; ns).

Research Question 5

Research questions 5 is: Which structure and process variables are most important in explaining job satisfaction? -Which variables of age, employment status, years of experience, and productivity are most important in explaining job satisfaction?

First, table 20 describes correlations of nurse characteristics and productivity with job satisfaction (the NWI-R). There was a weak, negative correlation (r=-.19; p=.03) of productivity with job satisfaction score from the NWI-R. Table 21 describes correlation of nurse characteristics and productivity with job satisfaction (overall job satisfaction).

There was no correlation between productivity and overall job satisfaction.

Next, multiple regression was used for variables (age, employment status, years of experiences, and productivity) predicting job satisfaction for the NWI-R (Table 22). The four independent variables did not explain a significant amount of variance (Adjusted

R2=.015; F=1.324; p=.27).

Then, multiple regression was used for variables (age, employment status, years of experiences, and productivity) predicting job satisfaction of the single item indicator, overall job satisfaction (Table23). The four independent variables did not explain a significant amount of variance (Adjusted R2=-.034; F=.220; p=.926).

Table20

Correlation of nurse characteristics and productivity with job satisfaction (the NWIR)

The NWIR Age Employment Experience Productivity

The NWIR 1.000 -.003 .114 .063 -.193*

Age 1.000 .067 .787*** .010

Employment 1.000 -.053 -.243**

Experience 1.000 .055

Productivity 1.000

Note. *p<.05; **p<.01; ***p<.001

Table21

Correlation of nurse characteristics and productivity with job satisfaction (the overall job satisfaction)

Overall Job Age Employment Experience Productivity

Satisfaction

JobSatisfaction 1.000 .015 -.067 .050 -.027

Age 1.000 .067 .787*** .010

Employment 1.000 -.053 -.243**

Experience 1.000 .055

Productivity 1.000

Note. *p<.05; **p<.01; ***p<.001

Table 22

Regression Analysis for Variables predicting job satisfaction (the NWI-R)

Unstandardized Unstandardized Standardized Partial Coefficients Coefficients Coefficients Correlations B Std. Error Beta Age -.131 .127 -.181 -.112

Employment Status 1.166 1.381 .094 .092

Years of Experiences .174 .139 .220 .136

Productivity -1.046 .636 -.181 -.178

Note. Dependent Variable: Total Score NWIR. F=1.32. Adjusted R2=.015; R2=.06

Table 23

Regression Analysis for Variables predicting job satisfaction (the overall job satisfaction)

Unstandardized Unstandardized Standardized Partial Coefficients Coefficients Coefficients Correlations B Std. Error Beta Age -.116 .422 -.048 -.029

Employment Status -2.967 4.574 -.071 -.068

Years of Experiences .231 .460 .087 .053

Productivity -.945 2.108 -.049 -.047

Note. Dependent variable: Satisfied with current job. F=0.22. Adjusted R2=-.034;

R2=.010

Summary

The purpose of this study was to identify productivity in home-visit nursing care

in Japan and to examine relationships between nurse characteristics, productivity, and job

satisfaction. The study sample consisted of 137 visiting nurses from the 28 Visiting Nurse

Stations (VNSs). Of this sample, 100 nurse surveys were returned for a response rate of

73.0 %.

For nurse characteristic, most subjects were female (98.0 %) and RNs (97.0%),

and graduated from diploma program (82.0%). More than half (60.2%) worked full-time.

Nurses were, on average 40.4 (SD=8.4) years of age.

Multiple regression was used to answer the research question 1 (Age, employment status, and years of experience associated with job satisfaction?). The findings indicated that age, employment status, and years of experience did not explain a significant amount of variance. Thus, nurse characteristics were not associated with job satisfaction.

Productivity was calculated to answer the research question 2 (What is the productivity of Japanese visiting nurses?). The results showed that productivity was 3.76

(SD=1.05) visits/day using the formula as previously stated and 52% of the time spent

was spent in direct care.

Multiple regression was used for variables predicting productivity to answer the

research question 3 (Are nurse characteristics associated with home-visit nursing care productivity?). The findings indicated that age, employment status, and years of

experience did not explain a significant amount of variance. Thus, nurse characteristics

were not associated with home-visit nursing care productivity. However, there was a

weak, negative correlation (r=-.24; p=.008) of employment status with productivity. 93

Pearson’s correlation was used for the research question 4 (Is home-visit nursing care productivity associated with job satisfaction?). There was a weak, negative correlation (r=-.19; p=.03) between productivity with the NWI-R.

Multiple regression was analyzed for the research question 5 (Which variables of age, employment status, years of experience, and productivity are most important in explaining job satisfaction?). Age, employment status, years of experience, and productivity did not explain a significant amount of variance for either dependent variable.

Chapter V

Discussion

This purpose of the study was to identify productivity in home-visit nursing care in Japan and to examine the relationships between nurse characteristics, productivity, and job satisfaction. This chapter includes a discussion of the study findings compared the results to past research, implications of the findings, limitations of the study, and suggestions for future research.

Discussion of Results

The Relationships between Nurse Characteristics and Job Satisfaction

Research question 1 asked “Are nurse characteristics (age, employment status, and years of experience) associated with job satisfaction?” The multiple regression results indicated that nurse characteristics (age, employment status, and years of experience) did not explain a significant amount of variance either, job satisfaction indicator (the NWI-R and the single item job satisfaction). This result is similar to previous studies that reported no relationship between nurse characteristics and job satisfaction (Ellenbecker, 2001; Anthony & Milone-Nuzzo, 2005).

In contrast to the studies (Ellenbecker, 2001; Anthony & Milone-Nuzzo, 2005) that found no relationship between nurse characteristics and job satisfaction, Navaie-

Waliser, Lincoln, Karuturi, & Reisch (2004) reported that newer employees (those employed less than 1 year) had more positive relationship with supervisors than staff who had been employed more than 1 year. According to Navaie-Waliser et al., the relationship with supervisors is an important indicator of job satisfaction, so longer term employees may be less satisfied with relationship with supervisors. Also, senior employees (those 95

employed for 6 or more years) ranked highly “recognition and acknowledgement” as an

important indicator of increasing job satisfaction. In contrast to these findings, in the

present study there was no correlation between years of experience and job satisfaction and there was no correlation between age and job satisfaction. There was a very weak, positive correlation (r=.114; ns) between employment status and job satisfaction (the

NWI-R). Although it was non-significant, employment status (part-time versus full time)

might be associated with job satisfaction from the result of a very weak, positive

correlation. Further research is needed to understand this finding in that the sample size

for the present study was sufficient for statistical power so if the relationship is present, it

should have been detectable.

Job Satisfaction

Many studies of nurse job satisfaction have been conducted in hospital settings

(Mueller and McCloskey, 1990; Whitley and Putzier, 1994), but research on job

satisfaction has only recently begun to be conducted in home health care settings

(Ellenbecker, 2001; Ellenbecker & Byleckie, 2005a & 2005b; Navaie-Waliser, Lincoln,

Karuturi, & Reisch, 2004; Smith-Stoner, 2004). The present study findings suggest that the NWI-R might be a useful indicator of job satisfaction in home health care settings in

Japan based on the following.

The NWI-R. In the present study, reliability of the NWI-R was assessed by using the Cronbach’s alpha for the overall scale (15 items of this version of the NWI-R) with an alpha of 0.82. The alphas of each subscale were 0.75 for autonomy, 0.62 for control, 0.79 for nurse-physician relationships, and 0.73 for organizational support. Previous research that reported the alphas of each subscale were 0.75 for autonomy, 0.79 for control, and 96

0.76 for nurse-physician relationships (Aiken et al., 2000). Thus, the results from the

present study are consistent with past reports of reliability indicating that the instrument

can be reliably used to measure job satisfaction and there is support to use the four

subscales of the NWI-R among home health care nurses in Japan as in the U.S.

Convergent validity of this version was assessed by correlation between the NWI-

R and the question on the VAS overall job satisfaction with r=0.47 (p<.01) or r2 = .22.

When there were higher scores of the NWI-R, there were higher ratings of the VAS overall job satisfaction, although much of overall job satisfaction is not explained by the

NWI-R because the correlation in the present study was lower between the NWI-R and

job satisfaction although the previous study had a strong correlation (r = -.65, p <.01)

between total scores of the NWI-R (Aiken et al., 2000) and the job satisfaction

(Yamashita, 1995).

The VAS overall job satisfaction was used to evaluate nurses’ satisfaction in the present study. The average job satisfaction rating was 62.5 (SD = 20.5; ranging from 0 to

100), so visiting nurses had relatively high satisfaction ratings. Their rating is lower than the previous study by Ellenbecker (2001) that identified the level of job satisfaction of

home health care nurses in the U.S. The average satisfaction score (21-item 5-point

Likert scale) was 82.17. Putting both studies on a 100 point scale results in a US average job satisfaction score of 72.8, higher than the average job satisfaction rating (62.5) in

Japan.

The NWI-R was used as the measure of job satisfaction. There were 15 items of this version of the NWI-R among visiting nurses in Japan. Subscales were scored as follows (Table 24): autonomy (total mean =15.1), control (total mean=18.2), physician 97 relationships (total mean=7.8), and organizational support (total mean=28.3) in the present study. Using the same 15 item version of the NWI-R, the Japanese home care nurses’ scores are compared to US nurses’ scores in home care and in hospital settings.

See Table 24. 98

Table 24

Comparisons between the NWI-R results in the present study and the previous study

Autonomy Control Physician Organaization-

relationships al support

M (SD) M (SD) M (SD) M (SD)

VNSs in Japan (The 15.1 (2.6) 18.2 (3.2) 7.8 (1.7) 28.3 (4.0)

present study)

U.S. home care 18.37(2.34) 24.83 (3.51) 10.65 (1.49) 32.24 (3.86)

(Flynn, et al., 2005)

U.S. hospitals 18.84 (2.21) 25.89 (3.13) 11.11 (1.37) 33.52 (4.00)

(Flynn, et al., 2005)

General Medical 17.0 (2.34) 22.7 (3.11) 6.5 (1.16) No reported Units Magnet Hospitals (Aiken, et al., 2000)

General Medical 14.2 (3.20) 17.4 (4.20) 5.8 (1.49) No reported Units Non-magnet Hospitals (Aken, et al., 2000)

Past research has found that using this version in American nurses, the scores

were different. The subscales for autonomy (M = 15.1) and control (M = 18.2) for

Japanese home care nurses were lower than hospital nurses in medical units in magnet

hospitals, but the subscale for physician relationships (M = 7.8) were higher. The relationships with physician are very important because visiting nurses need to receive

clinical orders from each physician for each patient in Japan. Moreover, all the subscale

scores for Japanese home care nurses were higher than hospital nurses in medical units in

non-magnet hospitals. Visiting Nurse Stations (VNSs) may not be non-magnet facilities.

Finally, all the subscale scores for Japanese home care nurses were lower than US home

care nurses. There are several plausible reasons for why Japanese home care nurses had

lower satisfaction than US home care nurses.

One explanation of lower scores of the NWI-R may be that Japanese VNSs are

smaller. In the present study, the average size of the VNS was 4.9 staff nurses (range 2 to

12). According to the regulations, a VNS can open in Japan with one top manager, one

staff nurse as full time, and one staff nurse as part time (half a day) (Social Insurance

Society, 2000). When the number of staff nurses is small, there are fewer staff available to take care of an increase in the number of patients or to cover other staff absences (like

vacation and holidays). In addition, staff in smaller VNS may not have the chance to

study new knowledge because their time is consumed with home visits.

In fact, many Japanese nurses in general are leaving their jobs, but the rate of

visiting nurses leaving their jobs at VNSs (13.2%) is higher than that of nurses at

hospitals (11.6%)(Japanese Nursing Association, 2004). Moreover, a survey on nursing

services in VNSs by the Japanese Nursing Association (2004) showed that 42% of the 100

VNSs answered that there was an inadequate number of visiting nurses. Thus the size of the VNS may be one explanation for the lower job satisfaction.

Another reason for lower satisfaction may be that the salary of a nurse who works at a VNS is lower than that of a nurse who works at a hospital (The Japanese Nursing

Association, 2004). The average reimbursement to the agency per visit is lower now than previously (Ogawa, 2002), so the salary differential may not be sufficient for the amount of time spent in indirect care.

The Productivity of Japanese Visiting Nurses

Research questions 2 asked “What is the productivity of Japanese visiting nurses?”

In the present study, productivity was 3.76 (SD=1.05) visits/day. Previous research showed the average productivity was 5.6 visits/day in the U.S. (Levy, 1979).

According to Banfield (1987), the national productivity standard for a registered nurse in home health was 5.7 visits/day in December of 1985. In Banfield’s (1987) article, national productivity standards in hospital-based home health agencies were as follows: registered nurse, 5.7 visits/day; psychiatric nurse, 3.4 visits/day; hospice nurse, 2.9 visits/day. Rozelle (1987) reported that the productivity (visits/day) of nursing was 5.7, the productivity of physical therapy was 4.5 and that of occupational therapy was 3.7.

Spoelstra (1996) compared productivity in 1987 and in 1996. While the number of actual visits per eight-hour workday was 5.02 in 1987, it was 5.73 in 1996. Thus, she showed that productivity (actual visits per 8-hour workday) increased from 1987 to 1996. The research shows that numbers of productivity from the above articles were all similar at

5.7 visits/day, the national productivity standards of the U.S. (December 1985) for a 101

registered nurse in home health (Banfield, 1987). There have been no recent reports on

US home care nurse productivity aside from anecdotal reports.

This number (3.76 visits/day) in the present study in Japan is less than that (5.7

visits/day) of the average productivity of registered nurses in the U.S. There are several

reasons for this is. First, the home care system is different in Japan. There are two main

types of insurance at home health care in Japan: the Long-Tem Care Insurance (LTCI)

and Medical Insurance. The LTCI system provides payment for three types of visits:

type1 [less than 30 minutes], type2 [from 30 less than 60], and type3 [from 60- less than

90]. Medical Insurance pays the same regardless if visit time is 30 minutes or 90 minutes.

Thus, the payment system in Japan pays differentially by the length of the visit for LTCI

whereas in the US, the payment system pays for the visit the same regardless of whether

the visit is 15 minutes or two hours.

Second, the formula used to calculate productivity is different. The average

productivity in the U.S. was shown as visits per day and does not include nonproductive

hours (the hours spent in indirect care). However, in the present study, nonproductive hours in addition to visits were included in the productivity formula. Thus, comparisons between the results in the present study and the previous study may not be comparable.

Both direct care and indirect care, such as travel, documentation, and telephone,

were measured in the present study. Visiting nurses spent, on average, 1018 (SD=454)

minutes for one week in direct care and, on average, 766 (SD=407) minutes for one week

in indirect care. Direct care is 57.8% of a visiting nurse’s week in Japan or a 58/42 ratio

of direct/indirect care time. This result is not similar to that the U.S where one study showed the proportion of direct care / indirect care is approximately a 45/55 for the home 102

care ratio in the U.S (Storfjell, 1989). Storfjell (1989) reported “Nonvisit-related time”

included documentation (20.5%), nonvisit coordination (14%), and travel (20.5%).

“Visit-related time” included assessment (15%), education (9%), physical care (8%),

psychosocial care (8%), and visit coordination (5%). Home health nurses spent more time on documentation and travel in the U.S. than nurses in Japan did.

In the present study, the percentage for the amount of indirect care time spent on each activity is the following: travel (41.5 %), documentation (20.2 %), telephone (4.5 %), meeting (14.4 %), preparation (8.0 %), and others (11.4 %). Travel is the largest time in indirect care in Japan, similar to the results reported by Storfjell. The caution is that the data for the Storfjell study is from more than 17 years ago and may not reflect current home care nursing practice.

productivity for nurses in home care were divided into 7 types: “client/family

management,” “practice management,” “knowledge/skill maintenance,”

“communication,” “nursing process,” “written documentation,” and “home health care

knowledge.” This result showed the productivity measurement classification for home health care nurses consisted of not only visits for client/family, but also paperwork. Both nonvisit work and visits are important to understand home care nursing practice. The results in the present study are similar in that nonvisit work is a significant portion of the time spent by home care nurses in Japan and are important in understanding the work environment of visiting nurses in Japan. 103

The Relationships between Nurse Characteristics and Productivity

Research questions 3 was “Are nurse characteristics (age, employment status, and years of experience) associated with home-visit nursing care productivity?” The multiple regression results indicated that nurse characteristics (age, employment status, and years of experience) did not explain a significant amount of variance, productivity. However,

there was a weak, negative correlation (r=-.24; p=.008) of employment status with

productivity such that those who worked more hours had more productivity. Nurses who

worked part time had less productivity. This reason for this is that the nurses working part

time have less time to work so the number of visits is less; this is not a surprising finding.

There are no studies in the US that examined this aspect. The closest study is from

more than 15 years ago and the results were similar to a study conducted by Hedtcke,

MacQueen, and Carr (1992) whereby the productivity of fee-for-visit nurses was 4.0

visits/day, while that of salaried nurses was 5.1 visits/day. In the study, a statistical

analysis was not conducted to compare the difference although a difference of 1.1

visits/day is substantively different. It showed that payment status may be related to

productivity.

Similarly, there is study by Feldman & Gurian (1988) who showed higher

productivity correlated with the length of experience in home care. When full time nurses

have more experience, they may have higher productivity. In the present study, the

average 15.0 (SD=7.8) years of experiences as full time nurses are longer than 14.2 (7.3)

years as part time nurses. Because the full time nurses have more years of experiences,

they may be more familiar with time management, and may know how to reduce non- 104

visit time. This may be another reason that nurses who worked as part time had less productivity.

The relationships between productivity and job satisfaction

Research questions 4 asked “Is home-visit nursing care productivity associated

with job satisfaction?” Pearson’s correlation showed that there was a weak, negative

correlation (r=-.19; p=.03) between productivity and the NWI-R. There is no previous

research on the relationships between productivity and job satisfaction. Most studies in

productivity have not used a statistical analysis: only descriptive information is shown that reports the number of visits per day. The results in the present study indicated that when there was higher productivity, there were lower scores of the NWI-R. Thus, the results suggest that nurses who have more productivity had lower satisfaction. One explanation is that many visits may lead visiting nurses to be more dissatisfied with their job because they need to have more time spent on indirect care (e.g. documentation, telephone, and meeting) for which they are not compensated. Conversely, the correlation is sufficiently small and when considering explained variance (coefficient of determination) in job satisfaction (r2), 3% of job satisfaction is explained by productivity.

Thus, there is much that is not understood.

The Relationships between nurse characteristics and productivity, and job satisfaction

Research questions 5 asked “Which variables of age, employment status, years of experience, and productivity are most important in explaining job satisfaction?” The multiple regression results indicate that nurse characteristics (age, employment status, and years of experience) and productivity did not explain a significant amount of variance in job satisfaction. There are a number of explanations for this lack of 105 significance. First, there is no reported research that used the formula of productivity which included indirect care time, so it is not possible to draw comparisons with US studies that report the number of visits per day. Second, the job satisfaction instrument is used at VNSs for the first time in Japan. While the reliability statistics were promising, the convergent validity finding indicates that much is not known about job satisfaction based on just the NWI-R. Thus, the variables selected for this analysis may not be the most important variables for understanding job satisfaction in Japanese home care nurses.

Implications for policy, theory and administration

Implication for policy

In the present study, home health nurses spent more time on travel than on any other indirect care activity. A better understanding of the components of travel time would be helpful in understanding how to reduce the travel time and thus increase the proportion of time spent in direct care. As well, how visiting nurses divide the patient visits is not well understood and there may be opportunities to reduce travel time by considering the assignments of patients to nurses such that nurses are working in smaller geographic areas. Japan is a densely populated; many Japanese live in high rise housing and there are traffic challenges. Thus, scheduling visits such that the visiting nurses can make best use of their travel may reduce the indirect care time. Also, nurses at VNSs often require face to face contact with physicians for obtaining prescriptions, thus strategically placing VNSs near hospitals may reduce the travel time for this function of the visiting nurse’s job.

While the Japanese Nurses Association calls for the establishment of more

Visiting Nurse Stations in Japan (Japanese Nursing Association, 2003), the number of 106

VNSs has not increased to meet the growing demand for care (Japanese Nursing

Association, 2003). The increase in the number of VNSs and visiting nurses has stalled, although the Japanese Nursing Association (2003) prioritized reinforcement of human resources in home-visit nursing care and expansion of the discretionary power of visiting

nurses. Visiting nurses are required to spend unpaid time to travel, make telephone calls

and coordinate care among other activities. However, visiting nurses are not reimbursed

for the indirect work they do once they have completed their home visits. Although

visiting nurses spend time working on patient care between visits, they are primarily

reimbursed for the actual time they spend at the patient’s home. Thus, the finding that

Japanese home care nurses spend almost half their time in unreimbursed activity may

explain the lower job satisfaction scores as compared to American home care nurses.

Reimbursement from the government for indirect care may be important to develop

VNSs in Japan. The issue about indirect care should be discussed and more research will

be needed to develop suitable reimbursement.

Moreover, the salary of a nurse who works at a visiting nurse station is lower than

that of a nurse who works at a hospital (The Japanese Nursing Association, 2004).

Although there is a need to establish more VNSs, visiting nurses are in short supply, and

moreover, more visiting nurses are leaving their jobs (Japanese Nursing Association,

2004). The amount of time spent that is unreimbursed may explain, in part, the stalling in

the number of VNS stations and nurses. Higher reimbursement may be needed to keep

salary of VNSs close to that of nurses at hospitals to prevent visiting nurses from leaving

their jobs. 107

Specifically, the NWI-R does not include measures of salary, uncompensated time

and the demands from being on call all the time. Thus, further instrument development is

needed to better understand how visiting nurses work and how they think about their jobs.

Qualitative research may be the best choice for this kind of instrument development .

Education. According to Japanese Nursing Association (2006c), the nursing

education system was changed in 1997. At that time, home health care education was

added for nursing students. However, the number of years of education required to be

registered nurses is still three years. The Japanese Nursing Association (2006c) suggested

years of nurse education should be more than four years. Thus, it is unclear whether

education for home health care is sufficient for nursing students. Research is needed to

determine the scope and length of home health care education for nursing students.

Implication for theory

None of the existing literature on workload study used a theoretical approach in

Japan, so this study pioneered how the Structure Process Outcome (SPO) Model could guide the choice of variables to include in the study in Japan. Depending on the study, many kinds of variables could be used in the SPO Model. The theory was useful in guiding the present study, although the lack of statistical significance suggests that further work in operationalizing the constructs and concepts is needed. The SPO Model

was useful to guide the study, but variables that were selected might not be suitable.

Although age, employment status, and years of experience as a nurse, as variables of

structure, were used in the present study, the result showed the lack of statistical

significance. Selection of variables in the model is important, and more research is

needed to develop the model in home health care area in Japan. 108

Implication for administration

The findings of the present study showed that employment status is weakly

associated with job satisfaction, and employment status is weakly related to productivity.

Also, the results in the present study indicated that when there was higher productivity, there were lower scores on the NWI-R. Thus, the results indicate when nurses have higher productivity, they have lower satisfaction. Many visits might make visiting nurses dissatisfied with their job. To increase job satisfaction, agency managers may consider

productivity of staff visiting nurses and employment status as factors that may influence

job satisfaction. As well, considerations of new models of providing care to reduce travel

and the other factors related to indirect care time may also be worth exploration.

Moreover, the result of lower scores on the organizational support subscale

implies that managers could provide better support for the staff nurses, although the types

of support that would benefit Japanese home care nurses is not clear.

Limitations

There were a number of limitations in this study. First, random sampling was not

done. A convenience sampling approach was used instead and there was a substantial

refusal rate. The investigator contacted top managers of 46 Visiting Nurse Stations

(VNSs) in Japan and 18 top managers of 18 VNSs refused to participate. Then 100 of

137nurses surveys from participating 28 VNSs were returned for a response rate of

73.0 %. Thus, the results may not be generalizable to the population of all visiting nurses

in Japan.

Second, the instrument developed and tested in one culture might not be able to

capture the same concept in Japan. There is little research on job satisfaction in home 109 health care, so the NWI-R was used in the present study. However, the NWI-R was developed in the U.S. and the instrument was used in home health care settings in the U.S. and other western countries. In Japan, the NWI-R has only been used in hospitals. For the first time in Japan, this version of subscales of the NWI-R was used at home health care settings in the present study. Flynn (2003) states that the practice environment of home care is different from that of hospitals and thus, the NWI-R might not be a sufficient measure of job satisfaction in home health care. This argument echoes the ongoing discussions about what the NWI-R actually measures. Some researchers argue that the

NWI-R measures aspect of the work environment or factors external to the individual while job satisfaction conceptually also may include factors internal to the individual.

Third, the time study component of the present study was based on nurse self- report. The investigator did not follow visiting nurses with a clock and did not measure the exact time that visiting nurses spent on direct and indirect care. It is also not clear whether this week represented a typical week or whether there were unusual events during the week the nurses recorded their time (e.g. vacations, sick days, holidays).

Suggestions for future research

The suggestions for future research focus on the next three studies based on the results of the study. First, a national survey should be conducted to evaluate VNSs in

Japan using a random sample of all VNSs in Japan. Then the results would be more generalizable to the population of all visiting nurses in Japan. As a result, government policymakers may then better understand the work environment of visiting nurses in

VNSs. 110

Second, an instrument focused on the work environment should be developed in

Japan. While the reliability and validity were sufficient, the lack of statistical significance

raises the issue of whether the NWI-R sufficiently captures the important aspects of job satisfaction for Japanese home care nurses. One approach would be to use a more qualitative approach and ask open-ended questions of Japanese home care nurses about what aspects of the job are associated with their satisfaction.

Third, the time study component should be conducted much more thoroughly.

One approach would be to follow existing guidelines for time studies to identify clearly the tasks done by visiting nurses during the course of their day. Because self-report is a concern, objective time measurements may be helpful in examining the time components.

Summary

The present study addressed what is productivity in home-visit nursing care in

Japan and how nurse characteristics and productivity might influence job satisfaction.

The results indicated that productivity was 3.76 (SD=1.05) visits/day, and that nurse characteristics (age, employment status, and years of experience) and productivity did not explain a significant amount of variance in job satisfaction. There are some implications of findings for policy, theory, and administration. A better understanding of the

components of travel time would be helpful in understanding how to reduce the travel

time and thus increase the proportion of time spent in direct care. The instrument should be developed for understanding how visiting nurses work and how they think about their working. The SPO Model was useful to guide the study, although the lack of statistical significance suggests that further work in operationalizing the constructs and concepts is needed. Also, the present study has some limitations regarding the generalizability, the 111 use of an instrument in VNSs, the use of formula of productivity including time spent on indirect care, and the use of the self-reported time study. Much more research is needed to understand job satisfaction and the work environment of VNSs to develop home health care in Japan.

112

APPENDIX

113

APPENDIX A Nurse Workload Form (B) Monday Direct care time (Time spent by visiting nurses in the patient’s home) Visits Actual Minutes Type of visits (circle one) during visits (1)LTCI [less than 30 minutes] (2)LTCI [from 30 less than 60] (3)LTCI [from 60 less than 90] (4)Medical insurance (5)Private payment (6)Others [ ] 1st minutes (1) (2) (3) (4) (5) (6)[ ] 2nd minutes (1) (2) (3) (4) (5) (6)[ ] 3rd minutes (1) (2) (3) (4) (5) (6)[ ] 4th minutes (1) (2) (3) (4) (5) (6)[ ] 5th minutes (1) (2) (3) (4) (5) (6)[ ] 6th minutes (1) (2) (3) (4) (5) (6)[ ] 7th minutes (1) (2) (3) (4) (5) (6)[ ] 8th minutes (1) (2) (3) (4) (5) (6)[ ] *Total time The investigator spent on Direct can calculate Care today here.

Indirect care time (The total time worked excluding direct care) Time spent on indirect care today Total minutes today Total time spent on travel (total minutes) Total minutes Total time spent on documentation (total minutes) Total minutes Total time spent on telephone (total minutes) Total minutes Total time spent on meetings (total minutes) (ex. Total minutes with staff. with medical doctors. with others.) Total time spent on preparation for visits (total Total minutes minutes) Total time spent on other activities (total minutes) Total minutes