2.1. Study Design, Study Site, and Population Characteristics
A cross-sectional study design was employed, and the study reporting adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for cross-sectional studies. The study was carried out in the Department of Orthopaedics of a tertiary care hospital in Jiangsu Province between June 2022 and June 2023. All patients included in this study were diagnosed with KOA, underwent TKA done by the same surgeon, and freely agreed to participate in the study.
Inclusion Criteria:
1. Speaking Chinese and being aged older than 60 years;
2. Meeting the diagnostic criteria for osteoarthritis of the knee as described in the Chinese guidelines for the diagnosis and treatment of osteoarthritis (2021 edition), with a Kellgren Lawrence classification of III-IV;
3. Having undergone unilateral TKA under general anaesthesia during hospitalisation (initial TKA on the operated side) >6 months ago;
4. Possessing normal abilities to understand information and communicate; n Knowing the details of the study and signing the informed consent form.
Exclusion Criteria:
1. Currently undergoing bilateral knee replacement or a postoperative revision for TKA;
2. Having malignant tumours or severe organ dysfunction;
3. Being elderly and unable to stand without assistance after surgery (assistive devices, such as canes or walkers, are permitted);
4 lost visitors.
2.2. Sampling Method and Technique
A convenience sampling technique was used to select participants who met the inclusion criteria. The sample size for this cross-sectional study wascalculated usingthe Kendal[15]sample size estimation formula: N = number of total variables*(5~10) times the total number of independent variables investigated, which is 15 in this study. According to the formula, the necessary sample size was calculated to be 75~150 cases, considering a 20% missed-visit rate, so the required sample size was considered to be 90~180 cases. A total of 175 questionnaires were distributed in this study, and 166 valid questionnaires were recovered, with an effective response rate of 94.86%.
2.3. Variables
After the literature review, the representative factors of each dimension of the HEM were initially organised. Using the focus group discussion method, influential factors that may affect sedentary behaviour among patients after TKA were included after two rounds of subject group validation in order to systematically explore the current situation and the factors influencing sedentary behaviour in elderly postoperative TKA patients. These factors included j Personal characteristics: age, gender, BMI, education level, and comorbidities; k Psychological and behavioural characteristics: preoperative sedentary lifestyle, knowledge of sedentary hazards, fatigue, and knee function; l Interpersonal network: marital status and social support; m Living and working conditions: Residential status, occupational status, and monthly income; n Policy environment: type of health insurance.
2.4. Instruments
2.4.1. Self-Designed Questionnaire for Sociodemographic and Clinical Characteristics
We obtained patients’ general demographic data from the electronic medical record system, including their gender, age, comorbidities, education level, monthly income, and type of medical insurance. Patients self-reported their marital status, occupational status, residential status, whether they had a sedentary lifestyle before surgery, whether they were aware of the dangers of sitting, and their height and weight for the calculation of their body mass index (BMI). According to the recommended BMI cut-off values <24 kg/m2, 24.0–27.9 kg/m2, and ≥ 28.0 kg/m2 for Chinese adults, patients were classified as underweight or normal weight, overweight, or obese, respectively[16].
2.4.2. Charlson Comorbidity Index (CCI)
The Charlson Comorbidity Index score was created by Charlson in 1987 [17]. It consists of 19 diseases and uses the patient’s underlying disease as the index for scoring, assigning different scores of 1, 2, 3, or 6 to each index, which are then added to create a total score of 0–36: The score is increased by 1 point for every 10 years of age over 40 years, with higher scores being associated with greater severity of comorbidities. Based on the questionnaire scores, the severity of comorbidities can be classified into three categories: mild (<3 points), moderately severe (≥3 points) [17].
The CCI has shown sound psychometric properties, including predictive, concurrent, and incremental validity. In addition, it has shown good inter-rater reliability, which was confirmed in the current study with an inter-rater reliability of 0.96.
2.4.3. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)
WOMAC was used to assess knee function in elderly post-TKA patients. The WOMAC was developed by Canadian scholars Bellamy[18]in 1988 and adapted for the Chinese context by Xie et al. It consists of the three dimensions of pain, stiffness, and difficulty with performing daily activities, with a total of 24 entries, and is rated on a 5-point Likert scale of 0 (no pain or difficulty) to 4 (extreme pain or difficulty), with higher scores indicating poorer knee function. The Cronbach’s α for the three dimensions of the Chinese version of the WOMAC scale were 0.82, 0.88, and 0.84, respectively[19]. The current WOMAC is one of the most commonly used patient-reported outcome measures.
2.4.4.Patient Self-Reported Sedentary Behaviour
The method of assessing sedentary behaviour used in Teychenne et al.’s study[20]was used to assess sedentary behaviour in this study, in which the study participants self-report their daily time spent sitting, including on transport, commuting to work, watching TV, using a computer/mobile phone, and taking other breaks (reading newspapers/books, playing cards, playing chess) during weekdays, as well as their daily time spent sitting during any of the abovementioned activities during the weekends, which was calculated by using the formula: daily sedentary time = (weekday sitting time × 5 + weekend sitting time × 2)/7. In this study, we referred to previous relevant literature [13,21]and defined behaviour as sedentary when the total sedentary time was ≥6 h/d and as non-sedentary when the total sedentary time was <6h/d.
2.4.5. Groningen Orthopaedic Social Support Scale (GO-SSS)
In 2004, Dutch scholars Akker-Scheek et al. developed the Groningen Orthopaedic Social Support Scale (GO-SSS) to assess the social support postoperative orthopaedic patients receive, and the Cronbach’s α coefficient of the scale was 0.89 [22].Adapted to the Chinese context by Sheng Xiaojuan et al. [23]the scale consists of 12 questions divided into two subscales: perceived social support (7 items) and instrumental support (5 items), both of which are rated on a four-point Likert scale, with answer categories ranging from “never” to “often”, with a total score of 0-3, in which a higher the score indicates better social support. The GO-SSS proved to be a reliable and valid instrument to assess social support for patients following arthroplasty, with a 0.863 Cronbach’s α for the entire questionnaire [24].
2.4.6. Lee Fatigue Scale (LFS)
The Chinese version of the Lee Fatigue Scale (LFS) was used to measure fatigue severity [25]. Fatigue severity was rated by seven items in the Chinese version of the LFS, rating each item on a numeric rating scale ranging from 1 to 10. A total score was calculated in the form of the mean of the seven items, with higher scores indicating greater fatigue severity. For this study, scores ≥5 were considered indicative of severe fatigue. The LFS has adequate psychometric properties[26] and is able to reduce the burden on the respondent. It is suitable for older adults and was chosen in consideration of the characteristics of the population included in this study.
2.5. Data Collection
The data collection method was jointly completed by two postgraduate students with unified training. Ten discharged post-TKA patients were selected for a pre-survey to assess whether the scale or questionnaire was easy for them to understand and to adjust any ambiguous or difficult statements. The pre-survey revealed that a significant proportion of the patient group were farmers, who were considered to be in a working condition in this study, and their level of physical activity was judged based on enquiries about their daily labour time and their degree of knee activity, and they were categorised as unemployed if their labour time and intensity were low. Patients were informed of the purpose and significance of the study when they were discharged from the hospital, promised that their information would be kept confidential and used only for this study, and all participants signed an informed consent form. Participants were surveyed and data were collected 6 months after surgery via telephone or WeChat (a social media and messaging application widely used in China) communication.
2.6. Ethical Considerations
Guided by the 2000 Declaration of Helsinki for ethical standards, the protocol was approved by the Committee on the Ethics of Medical Research of the investigating hospital (2023-03-035-K01). Informed consent was provided by all participants prior to their participation. The survey was anonymous, and the confidentiality of the information was assured.
2.7. Validity and Reliability/Rigor
The study was conducted and reported under the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies.
2.8. Statistical Analysis
The collected data were entered and analysed using SAS 9.4. The Shapiro-Wilk method was used to test the normality. The measurement data of the normal distribution were represented by mean ± standard deviation ( ), and the comparison between the two groups was performed by an independent sample t test. The measurement data of the non-normal distribution were represented by M (P25, P75), and the rank sum test of two independent samples (Mann-Whittney U test) was used to compare the two groups. Descriptive analyses were performed using frequencies and percentages, and the χ2 test was used to compare statistical data between groups. The statistically significant indicators after the single-factor analysis were incorporated into the multi-factor logistic regression model to identify the risk factors of sitting for too long. A p value <0.05 was considered statistically significant.