Eligible participants were nursing staff who provided direct patient care during three weeks between October 2018 and January 2019. Other facility staff, such as physicians,
occupational therapists, physiotherapists, and activity staff, were excluded because they spend less time with residents. A three-week data collection period was chosen to embrace nursing staff working different hours per week at the nursing home.
4.2.1 Sampling Design and Sample Size
The current study uses a multistage sampling design, with nursing homes recruited in the first stage, and nursing staff working in these nursing homes recruited in the second stage. A multistage sampling technique is a cost-effective and often-used method to cover large geographical areas (e.g., in national surveys; Lewis-Beck et al., 2004). In the field of elder abuse, standardized measurement instruments are lacking, and few large national studies have been conducted to explore its magnitude (Malmedal et al., 2020). The sample sizes of nursing homes and staff in the current study were not statistically computed. After discussing with statisticians at the unit for Applied Clinical Research (ACR), NTNU, and Statistics Norway and reviewing the sample size and response rates in the few existing national studies, a sample of approximately 10% (N = 100) of all Norwegian nursing homes was chosen. In comparison, the national survey on staff-to-resident interactions and conflicts in Ireland included 64 out of 613 nursing homes (Drennan et al., 2012).
In Norway, the Central Register of Establishments and Enterprises (CRE) contains information of all enterprises (juridical units) and establishments in the private and public sectors, and a simple random sampling technique of all nursing homes registered in the CRE was applied. The register from 2017 was first sorted by industrial codes 87.102 (somatic
39 nursing homes) and 87.301 (retirement homes; hereafter nursing homes), which resulted in 939 institutions, excluding two nursing homes used in the pilot of this study. Then, the unit for ACR used a computerized random number generator to draw a sample of 100 nursing homes. This initial procedure resulted in 49 nursing homes with ≥ 34 beds, the median number of beds in Norwegian nursing homes (Statistics Norway, 2017), and 51 institutions with < 34 beds. To compensate for nursing homes declining to participate, the ACR also randomly drew 50 nursing homes to act as reserve homes.
Of the initially 100 invited nursing homes, 27 declined participation, of which many were above the median size of 34 beds. To prevent further skewness, the reserve list was sorted by size, and the 30 largest nursing homes were initially invited, whereas 27 accepted
participation (Figure 3). The sample population of nursing homes ranged in size from eight to 161 beds (median 38.5), where 42% were located in suburban areas, 31% in urban areas, and 27% in rural areas, covering all counties in Norway. Ninety-four percent of nursing homes were publicly run by municipalities and 6% by private organizations, approximately reflecting the public/private ratio of nursing homes in Norway.
Figure 3. Flowchart of the Recruitment of Nursing Homes and Nursing Staff (Paper I)
40 4.2.2 Data Collection
The data collection procedure was similar to the Norwegian study on elder abuse conducted by Malmedal et al. (2009a). To recruit nursing homes, an invitation letter was emailed to each nursing home director, followed by a telephone call. Directors accepted by email, along with providing the estimated number of staff at work for three weeks and the name and contact information of one “coordinator” who could administer the survey on site. This task was assigned to either ward managers, nursing home directors, or others appointed by the directors. Each coordinator was provided with a box that included an instruction letter, information/motivation posters, staff questionnaires with information and an invitation letter on the front page (Appendix I), two short questionnaires concerning the unit and facility to be completed by unit managers (Appendix II) and nursing home director (Appendix III), sealed collection box(es), and prepaid postage for the return of the sealed collection box(es). The instruction letter described in detail how the coordinators should administer the survey on site: a) provide information to staff via email and in formal/informal meetings; b) place information/motivation posters in staff duty rooms and wardrobes; c) distribute staff
questionnaires in mail shelves and inform staff to place the completed questionnaires directly in the sealed collection box(es); d) send at least two reminders by email; e) after three weeks, write down the exact number of nursing staff at work during the study period; and f) pack and send the sealed collection box(es) with the prepaid postage to NTNU. The coordinators were informed that they could contact the doctoral candidate at any time.
4.2.3 Response Rate
A total of 6,337 nursing staff were eligible for inclusion, whereas 3,811 returned survey questionnaires, resulting in a response rate of 60.1%. Of these, 118 participants were excluded because they did not work in direct care, worked in daycare centers or assisted living facilities, or had not answered any items concerning elder abuse. The nursing home participation rate was 73%, which is higher than Pillemer and Moore (1989) and Castle (2012b). Overall, 3,693 nursing staff were included, resulting in an analytic response rate of 58.3% (Figure 3).
Response rates in surveys of healthcare professionals are often low, and non-responders may be systematically different from responders, which increases the potential for bias and may threaten validity. However, researchers use a wide range of methods to calculate these response rates, and no agreed-upon standard acceptable rate exists (Draugalis et al., 2008).
41 Hence, of equal importance to the response rate itself is the transparency of the recruitment process (Draugalis et al., 2008). Cook et al. (2009) analyzed response rates in 350 postal or electronic surveys of healthcare personnel from 1996 to 2005 and found an average response rate of 56%, with only 16% of studies achieving a response rate of 75% or higher. The analysis also revealed that the highest response rates were found in studies using reminders, in studies with less than 1,000 respondents, and studies conducted in countries other than the US, Canada, Australia, or New Zealand.
Reasons for study participation vary; some people are stimulated by the purpose, and others respond because surveys are short in length (Groves & Peytcheva, 2008). Monetary
incentives may enhance response rates, and some elder abuse studies have provided incentive gift cards directly to nursing staff and obtained high response rates (Castle, 2013). Others have achieved high response rates without incentives, but with a thorough data collection procedure (Malmedal et al., 2009a). In this study, nursing staff received no direct payment, but the eight nursing homes with the highest response rates were offered an economic incentive of approximately 900 GBP dedicated to the welfare of staff. The response rates of nursing homes varied from 14% to 100%, where nine institutions had a rate below 30%, and 46% of nursing homes achieved a response rate above 75%.