Development and Validation of the Out-of-Hospital Adherence Questionnaire for Stroke Patients

doi:10.21203/rs.3.rs-5000451/v1

Background

The extent of rehabilitation of stroke patients outside the hospital is contingent upon their dedication to rehabilitative exercises, adherence to a suitable diet, and medication protocols. Therefore, multiple aspects of compliance must be assessed. Questionnaires are indirect measurements that are economical and easy to use. However, questionnaires should meet specific criteria to minimize errors and ensure reprehensibility of the results.

Objective

To evaluate the psychometric properties and feasibility of an Out-of-Hospital Adherence Questionnaire for Stroke Patients, which has at least one measure of validity and one measure of reliability.

Methods

A preliminary "Out-of-hospital Adherence Questionnaire for Stroke Patients" was developed based on a literature review and two rounds of Delphi expert consultation. Between April 1 and July 2022, 308 stroke patients revisited the neurology departments of four Grade A tertiary hospitals in Shanghai using the convenience sampling approach. Various statistical methods, such as item analysis, correlation analysis, exploratory factor analysis, confirmatory factor analysis, and the internal consistency measure Cronbach’s α coefficient, were employed to assess the reliability and validity of the questionnaire.

Results

A total of 290 questionnaires were collected; the Cronbach’s α coefficients were 0.936, 0.862, 0.916, and 0.928 for the different sections, and the overall Cronbach’s α coefficient for the entire scale was 0.902. The results of the confirmatory factor analysis were CMIN/DF = 2.490, RMR = 0.05, GFI = 0.901, NFI = 0.927, IFI = 0.955, and RMSEA = 0.054. The standardized loading values varied between 0.717 and 0.916. The combined reliabilities of the four dimensions were 0.936, 0.864, 0.917, and 0.929, respectively. The average variance extraction values for the four dimensions are 0.676, 0.614, 0.611, and 0.652, respectively.

Conclusion

The Out-of-Hospital Adherence Questionnaire for Stroke Patients is a reliable and accurate instrument for evaluating medication use, nutritional status, and behavior throughout the out-of-hospital rehabilitation phase.

validation

stroke

adherence

scale

validity

reliability

The increase in the global population has led to an increased incidence of chronic conditions, such as cerebrovascular disease, which poses a significant health threat to elderly individuals in China.¹ The Global Burden of Disease (GBD) study identified stroke as the primary cause of disability among adults.² Given the upward trajectory of stroke incidence, the number of annual stroke-related deaths in China is projected to reach 4 million by 2030. Inadequate efforts to prevent and manage stroke may impose considerable financial strain on families³^,⁴

Presently, there is a notable reduction in mortality rates among stroke survivors, accompanied by a marked increase in overall survival rates. However, the prevalence of hemiplegia and disability remains high. Approximately 35% of individuals who have survived ischemic stroke are unable to achieve full physical recovery, with 20–25% requiring substantial assistance for mobility.⁵ Of this population, 40% were classified as being severely impaired.⁶ Patients with recurrent stroke often face a higher risk of long-term disability characterized by more severe paralysis and cognitive impairment than those who have experienced their initial stroke⁷^,⁸ and the risk of stroke recurrence is most significant within the first year after the initial event, with a recurrence rate of 10%. Furthermore, the overall probability of stroke recurrence within a five-year timeframe was 25%.⁹

The Chinese Guidelines for Stroke Prevention and Control (2021 edition) outline a comprehensive framework for implementing standardized measures for primary and secondary prevention.¹⁰ Emphasizing the importance of efficient nursing and rehabilitation guidance, the guidelines suggest that combining these strategies can be a highly effective approach for preventing stroke. Additionally, the guidelines underscore the significance of enhancing patient adherence through health promotion programs involving the patient's family. Adherence, as defined by the World Health Organization (WHO), refers to the extent to which an individual follows medical recommendations provided by healthcare professionals regarding diet, medication, and lifestyle changes.¹¹ Poor adherence is often linked to various factors including socioeconomic, treatment-related, individual patient-related, environmental, and healthcare system-related issues.¹²⁻¹³ Furthermore, multiple studies have demonstrated a clear and significant correlation between adherence and prognosis in stroke survivors.¹⁴⁻¹⁵ Therefore, it is essential to promptly and accurately assess the adherence of patients with stroke during the rehabilitation phase.

The General Adherence Scale (GAS) and Morisky Self-reported Adherence Questionnaire (MAQ) are frequently used to assess adherence in stroke patients. The GAS, comprising five items, was specifically designed to assess overall adherence patterns in patients with chronic illnesses over a four-week period.¹⁶ The GAS showed good stability, internal consistency (alpha coefficient = 0.81), and reliability (0.4).¹⁷ This instrument is commonly used in international settings.¹⁸^,¹⁹ Another notable survey instrument is the MAQ, which comprises four items designed to evaluate individuals' likelihood of discontinuing medication in specific scenarios and their ability to adhere to their prescribed regimen.²⁰ This scale is user friendly, making it accessible to patients with varying levels of literacy. Its applicability is also versatile, and it has demonstrated strong reliability and validity (Cronbach's α = 0.76) when used among individuals with hypertension in China²¹^,²²^,²³ Moreover, self-report observational techniques can be utilized to evaluate adherence to daily behavior modification²⁴^,²⁵ and the Stroke Behavior Change Questionnaire, developed by Sullivan et al., to assess the extent to which patients alter modifiable risk variables before and after experiencing a stroke.²⁶ Jingjin et al. (2010) translated and adapted this questionnaire to assess the extent to which community-dwelling geriatric stroke patients adhere to treatment.²⁷

Currently, questionnaires designed exclusively for stroke patients are restricted to evaluating medication adherence or individual behavioral modifications. However, the extent of rehabilitation for stroke patients outside the hospital is contingent upon their dedication to rehabilitative exercises, adherence to a suitable diet, and medication protocols. Hence, measuring the adherence of out-of-hospital stroke patients based solely on a single assessment criterion is inadequate. The objective of this study was to evaluate the precision of a dedicated out-of-hospital adherence questionnaire tailored to Chinese stroke patients. The primary objectives of this study were to develop a more succinct iteration of the questionnaire, evaluate its capacity to gauge the same concepts as other well-established assessments, and validate the structure and precision of the questionnaire using confirmatory factor analysis.

Study Design and Process

The questionnaire development process consisted of the following three stages.

Establishment of a questionnaire development working group

The working group for this study included decision-makers, researchers, and nursing management staff from various institutions, including Fudan University, Shanghai Traditional Chinese Medicine University, and Shanghai University of Medicine and Health Science. In addition, experts from multiple disciplines, such as epidemiology, evidence-based medicine, evidence-based social sciences, public health management, health policy, and health education, were recruited to ensure that a wide range of perspectives was represented during the development of the questionnaire.

Conceptual framework and Main concepts

The prevailing concept of patient adherence refers to a patient's adherence to prescribed behaviors, including medication intake, food regulation, lifestyle adjustments, and regular attendance at medical visits, thereby establishing a compliant rapport between the patient and healthcare provider.

The theory of planned behavior (TPB) is a theoretical framework that elucidates and forecasts individual behavior. The theoretical model exerts an impact on real behavior through behavioral attitudes, norms, and perceptions.²⁸ The idea of planned behavior has been widely used across various disciplines and has strong explanatory power. This study could offer a theoretical framework for administering an out-of-hospital adherence questionnaire (Fig. 1).

Determination of the content of the questionnaire items

This study relied on the definition of adherence, theory of planned behavior, Medication Adherence Self-efficacy Scale, Chinese guidelines for stroke rehabilitation treatment, and Recommendations for Exercise for Stroke Patients issued by the American Heart and Stroke Association ( AHA) in 2014. Following the group discussion, a 28-item questionnaire was created to assess adherence in stroke patients. The questionnaire consisted of 8 items related to medication adherence, 5 items related to self-monitoring adherence, 8 items related to rehabilitation adherence, and 7 items related to adherence to lifestyle and behavioral modifications.

Experts’ consultation

Experts from pertinent disciplines were invited to assess the initial version of the questionnaire in two rounds of consultation with the aim of enhancing its precision. In the initial phase, specialists were asked to evaluate the essentiality, significance, achievability, and comprehensibility of each element in the survey using a five-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, and 5 = strongly agree). Additionally, they had the opportunity to offer recommendations for altering particular elements or for the questionnaire as a whole. Items with mean scores of 3.5 or higher and full score ratios of 0.2 or higher were retained, while items with lower scores were either adjusted or removed based on the findings of this round.

In the second round, experts were tasked with assessing the pertinence of dimensions to subjects and things using a four-level Likert scale ( scores ranging from 1 to 4 indicate varying degrees of irrelevance to high relevance). An item-level content validity index(I-CVI) was computed to determine the content validity index at the item level. The scale was adjusted for expert probabilistic consistency (Pc), and the validity of the questionnaire was evaluated using modified kappa statistics (K∗). An I-CVI score equal to or greater than 0.78 and a K∗ value ranging from 0.60 to 0.74 were considered to indicate strong content validity. A K∗ value over 0.74 indicated exceptional validity.²⁹^,³⁰

Validation

The validation study was conducted in Shanghai, China between April 1 and July 1, 2022. To achieve a heterogeneous sample, individuals were selected from multiple medical establishments, including the Shanghai Hospital of Traditional Chinese Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shuguang Hospital, Longhua Hospital, and Huashan Hospital Fudan University. Participants were recruited via convenience sampling, considering factors such as age, sex, and other relevant characteristics. First, the target sample size of 280 participants was determined, approximately ten times the number of questionnaire items. To compensate for potential omissions in interviews and unreliable surveys, the sample size was increased by 20%, yielding the desired sample size of 308 participants. The inclusion criteria for patients were as follows: (1) history of transient ischemic attack (TIA) or stroke, (2) proficiency in language and effective communication, and (3) willingness to participate in this research. The exclusion criteria for patients were as follows: (1) severe complications, cognitive impairment, or mental disorders; (2) visual or mental impairments that hindered their ability to complete the assessment; (3) employment in medical, nursing, or other healthcare-related fields; and (4) voluntary withdrawal from the study for any reason.

Survey methods and quality control

The six subject investigators were divided into three pairs and underwent relevant training in their respective areas of expertise. Before administering the survey, the goals and substances of the study were comprehensively elucidated to the participants. After providing consent from the participants, the researchers proceeded to ask the questions individually, giving the participants the option to answer independently or provide verbal guidance to the researchers while recording their responses. Upon completion, all questionnaires were promptly collected and the data were input into the study database using MS Office Excel on the same day. The research group subsequently conducted a questionnaire validation on the day of data collection to identify and eliminate any replies that were deemed invalid or incomplete to ensure the general validity of the data.

Statistical analysis

The level of agreement across expert viewpoints was measured using the coefficient of variation (CV) and the Kendall harmonic coefficient (KW). The significance of the Kendall harmonic coefficient was assessed using the χ2 test. The total Kendall coordination coefficient had a significance level of P < 0.01, suggesting a strong level of coordination. The expert authority coefficient (Cr) was calculated as the average of the judgement basis coefficient (Ca) and the familiarity coefficient (Cs). The data obtained from the validation research were analyzed using the statistical software SPSS 26.0. Counts were represented by their frequency and percentage, whereas quantitative data were represented by the mean value plus or minus the standard deviation. Content validity, internal consistency, and test reliability were assessed using the item-level content validity index (I-CVI), Cronbach's alpha coefficient, McDonald's omega, and intraclass correlation coefficient (ICC), respectively. Construct validity was evaluated using exploratory factor analysis (EFA).

Ethics approval

The study was carried out in strict adherence to the principles of voluntariness, secrecy, and respect for human subjects, ensuring the protection of respondents' legitimate rights and interests.

Questionnaire development

A total of 2152 documents were obtained, and 763 documents were selected, including 345 in Chinese and 418 in English. The entry pool consists of 46 entries. Following group discussions and expert consultations, a thorough review resulted in manual removal of 18 duplicate and similar items. Consequently, an initial Out-of-Hospital Adherence Questionnaire consisting of 28 items was developed. This questionnaire included 8 items related to medication adherence(A), 5 items related to self-monitoring adherence(B), 8 items related to rehabilitation adherence(C), and 7 items related to adherence to lifestyle behavior changes(D). Each question was formatted as a single-choice one (Fig. 2).

Expert consultation and content validity

A total of 15 experts in related fields were consulted in the first round, including experts in health communication, behavioral science, public health policy, health promotion, stroke disease prevention and control, health career management, basic medical education research, and nutrition and health. The average number of years was 24.2 ± 6.89 (Table 1).

Table 1 Characteristics of the experts（n=15）

Characteristic	No. of experts	Proportion(%)
Gender
Male	2	13.33
Female	13	86.67
Age
26～30	1	6.67
31～40	2	13.33
41～50	9	60
51～60	3	20
Education
Bachelor’s degree and blow	10	66.67
Master’s degree	1	6.67
Doctorate degree	4	26.67
Professional title
Senior	3	20
Vice-senior	5	33.33
Middle	7	46.67
Primary	0

The Ca values in the two rounds of correspondence in this study were 0.85 and 0.87, respectively. The experts' familiarity with the Cs values were 0.88 and 0.89, respectively. The experts' Cr values were 0.87 and 0.88, respectively. All 15 experts were found to have high Cr values based on their self-identification. The Ca value ranged from 0.7 to 1.0, while the Cs value ranged from 0.8 1.0. The level of expert authority was deemed high.

KW values were calculated for each factor, yielding KW(A) = 0.344, KW(B) = 0.525, KW(C) = 0.299, and KW(D) = 0.282. The results were statistically significant (P < 0.01), indicating a high level of agreement among experts. The level of consensus among the expert viewpoints was deemed satisfactory, as all the scores were less than 0.25. Furthermore, the questionnaire underwent a second round of modifications in which expert viewpoints were incorporated to make the necessary deletions.

The second round of the expert consultation form involved 27 items across four dimensions. The KW values for each dimension were as follows: KW(A) = 0.533, KW(B) = 0.573, KW(C) = 0.575, and KW(D) = 0.672 (P < 0.05). One entry from the life behavior change adherence dimension that did not match the criteria was ultimately removed, resulting in 26 entries in the preliminary questionnaire (Table 2).

Table 2

The degree of coordination between the two rounds of expert opinions
Round	Dimensions	Items	Number of experts	CV	KW		P
Round 1	Medication Adherence	8	15	0.072	0.344	36.165	<0.001
	Self-monitoring Adherence	5	15	0.079	0.525	31.489	<0.001
	Rehabilitation Adherence	8	15	0.051	0.299	31.355	<0.001
	Life behaviors change Adherence	7	15	0.096	0.282	25.346	<0.001
Round 2	Medication Adherence	8	15	0.078	0.533	48.000	<0.001
	Self-monitoring Adherence	4	15	0.054	0.573	34.370	<0.001
	Rehabilitation Adherence	7	15	0.094	0.575	51.745	<0.001
	Life behaviors change Adherence	8	15	0.077	0.672	70.583	<0.001

Validation of the questionnaire

Questionnaire population validation analysis

To refine the questionnaire, 20 stroke patients who underwent a follow-up assessment in the neurology department of the previously mentioned hospital were randomly chosen for the preliminary survey. The questionnaire has a validity rating of 100%. A total of 12 males and 8 females were included, and the mean age was 61.38 ± 5.83 years. The questions were answered within approximately 7 minutes. The surveys have been revised and modified accordingly. The questionnaire consisted of 26 items distributed across four dimensions, with eight, four, seven, and seven items.

A standardized questionnaire was used to assess patients with stroke who underwent a follow-up assessment in the neurology department of the previously mentioned hospital. A total of 308 participants were included, 290 of whom were considered legitimate. This resulted in a valid recovery rate of 94.16%. A total of 170 males and 120 females participated in this study. The mean age was 59.03 ± 6.11 years. The majority of the patients had literacy levels equivalent to elementary school or junior high school. Married patients constituted 89.66% of the total patient population. Patients’ medical expenses were predominantly reimbursed by China's healthcare insurance (Table 3).

Table 3

General characteristics of stroke patients(n = 290)
Descriptions	No. of respondents	Proportions(%)
Gender
Male	170	58.62
Female	120	41.38
Age
<50	35	12.07
51ཞ60	83	28.62
61ཞ69	132	45.52
≥ 70	40	13.79
Education
illiteracy	16	5.52
Elementary or middle school	117	40.34
senior secondary	108	37.24
University or above	49	16.90
Matrimonial
married	260	89.66
divorcee	16	5.52
widowhood	5	1.72
unmarried	9	3.10
Occupation
incumbency	37	12.76
unemployed	62	21.38
retired	124	42.76
others	67	23.10
Residency
countryside	60	20.69
towns	164	56.55
municipalities	66	22.76
Combined chronic diseases
one	147	50.69
two	108	37.24
three or above	35	12.07
First-ever stroke
yes	124	42.76
no	166	57.24
Type of medical insurance
urban residents	133	45.86
New Rural Cooperative Medical Care	89	30.69
others	68	23.45
Residence
solitary	101	34.83
cohabitation	189	65.17
(fig.) Repercussions
yes	95	32.76
no	140	48.27
yes, but recovered	55	18.97
Time of first onset
<one month	94	32.41
1–6 months	158	54.49
> 6months	38	13.10
Incomes
<1000 CNY	44	15.17
1001–3000 CNY	78	26.89
3001–6000 CNY	69	23.80
6001–10000 CNY	53	18.28
10001–20000 CNY	32	11.03
> 20000 CNY	12	4.14
don't know.	2	0.69

Questionnaire discrimination and homogeneity analysis

The study used a sample of 100 questionnaires from 290 participants. The critical ratio t-test method was employed, employing a grouping criterion of 27% based on the difference in total scores. Two independent-sample t-tests were conducted to determine whether there was a significant difference between the high- and low-risk groups. Typically, the disparity in scores between the two groups is not statistically significant, or the t-value falls below 3, which is the threshold for exclusion. The results indicated that there were no statistically significant differences between the A3, A8, B1, and C5 scores. Consequently, the research team opted to exclude A8 from the dataset while retaining the remaining three entries. All remaining entries had a t value greater than 3, indicating that the questionnaire exhibited a high level of differentiation. All the Pearson correlation coefficients for the total correlation question were above 0.4, suggesting that each item had a high level of internal consistency and that the questionnaire demonstrated good homogeneity³¹ (Table 4).

Table 4

Analysis of the total correlation of the questions
Item	r	P	Item	r	P
A-1	0.622	<0.001	C-3	0.488	<0.001
A-2	0.585	<0.001	C-4	0.451	<0.001
A-3	0.568	<0.001	C-5	0.583	<0.001
A-4	0.611	<0.001	C-6	0.457	<0.001
A-5	0.580	<0.001	C-7	0.438	<0.001
A-6	0.682	<0.001	D-1	0.282	0.003
A-7	0.626	<0.001	D-2	0.275	0.004
B-1	0.512	<0.001	D-3	0.455	<0.001
B-2	0.580	<0.001	D-4	0.402	<0.001
B-3	0.639	<0.001	D-5	0.34	<0.001
B-4	0.569	<0.001	D-6	0.486	<0.001
C-1	0.504	<0.001	D-7	0.572	<0.001
C-2	0.433	<0.001

Questionnaire validity analysis

Exploratory factor analysis of the questionnaire yielded a KMO value of 0.923 and an approximate chi-square value of 8964.138, with a significance level of P < 0.001. These results indicate that the out-of-hospital adherence questionnaire for stroke patients was successful after factor analysis and variable extraction. The questionnaire identified four factors that did not have multivariate loading. The dimensions had high loadings on their respective factors, suggesting that the results of the exploratory factor analysis were consistent with the original design of the scale. This indicates that the questionnaire had good structural validity (Table 5).

Table 5

Analysis of exploratory factor
Dimension	Item	Element
Dimension	Item	1	2	3	4
Medication Adherence	A-1	0.883	0.041	0.020	0.225
	A-2	0.827	0.049	0.044	0.208
	A-3	0.796	-0.037	0.027	0.110
	A-4	0.825	0.045	0.061	0.141
	A-5	0.812	-0.008	0.044	0.141
	A-6	0.830	-0.015	0.027	0.158
	A-7	0.852	-0.025	0.070	0.160
Self-monitoring Adherence	B-1	0.395	0.005	0.115	0.683
	B-2	0.279	0.017	0.146	0.797
	B-3	0.236	0.032	0.137	0.822
	B-4	0.210	0.065	0.169	0.810
Rehabilitation Adherence	C-1	0.025	0.122	0.748	0.196
	C-2	0.017	0.114	0.751	0.141
	C-3	0.028	0.161	0.798	0.088
	C-4	0.056	0.150	0.804	0.109
	C-5	0.043	0.198	0.818	0.053
	C-6	0.054	0.211	0.814	0.053
	C-7	0.086	0.158	0.816	0.010
Life behaviors change Adherence	D-1	0.023	0.722	0.315	0.083
	D-2	0.007	0.774	0.244	0.064
	D-3	-0.007	0.828	0.162	0.006
	D-4	0.012	0.837	0.155	0.018
	D-5	-0.052	0.844	0.093	0.015
	D-6	0.009	0.859	0.109	-0.033
	D-7	0.050	0.865	0.110	0.021

Furthermore, the results of the factor analysis model validation for the questionnaire indicated that the CMIN/DF value was 2.490, RMR was 0.05, GFI was 0.901, NFI was 0.927, and IFI was 0.955. All of these values met the criteria for an excellent model fit. Additionally, the RMSEA value was less than 0.08, which is considered a good standard for a model fit. These findings suggest that the factor analysis model used in this study is well suited. The questionnaire demonstrated strong aggregate validity, as indicated by standardized loading values ranging from 0.717 to 0.916 across the four dimensions (Table 6 and Fig. 3).

Table 6

Analysis model of adaptation of validating factor
Fit index	CMIN/DF	RMR	GFI	CFI	NFI	IFI	RMSEA
Standard	<3	<0.05	>0.9	>0.9	>0.9	>0.9	<0.05 excellent <0.08 good
Results	2.490	0.05	0.901	0.955	0.927	0.955	0.054

Convergent validity measures the degree of agreement between the different aspects of the underlying variable. When examining the four dimensions, the standardized loadings for the measurement items varied from 0.717 to 0.916, all of which were greater than 0.7. The combined reliabilities of the four dimensions were 0.936, 0.864, 0.917, and 0.929, all greater than 0.7. Additionally, the average variance extracted (AVE) values for the four dimensions were 0.676, 0.614, 0.611, and 0.652, all of which exceeded 0.5. Hence, the overall reliability of the questionnaire was satisfactory (Table 7).

Table 7

Analysis of aggregation validity
Item	Non-Standardized Factor loading	Standardized Factor loading	Std. Error	t	Combinatorial reliability	AVE
Medication Adherence
A-1	1	0.916			0.936	0.676
A-2	0.884	0.853	0.031	28.507***
A-3	0.802	0.746	0.037	21.810***
A-4	0.850	0.790	0.035	24.252***
A-5	0.830	0.782	0.035	23.768***
A-6	0.863	0.811	0.034	25.587***
A-7	0.926	0.847	0.033	28.066***
Self-monitoring Adherence
B-1	1	0.737			0.864	0.614
B-2	1.062	0.815	0.061	17.365***
B-3	1.071	0.800	0.063	17.072***
B-4	1.023	0.780	0.061	16.667***
Rehabilitation Adherence
C-1	1	0.729			0.917	0.611
C-2	1.024	0.717	0.065	15.852***
C-3	1.125	0.782	0.065	17.347***
C-4	1.155	0.795	0.065	17.644***
C-5	1.105	0.818	0.061	18.191***
C-6	1.181	0.824	0.065	18.313***
C-7	1.124	0.801	0.063	17.790***
Life Behavior Change Adherence
D-1	1	0.729			0.929	0.652
D-2	1.046	0.767	0.061	17.170***
D-3	1.051	0.815	0.057	18.311***
D-4	1.090	0.828	0.059	18.622***
D-5	1.118	0.811	0.061	18.212***
D-6	1.139	0.840	0.060	18.915***
D-7	1.157	0.854	0.060	19.235***

Discriminant validity analysis revealed that the bold numbers represent the square root of the mean variance recovered for each dimension, while the other numbers indicate the correlation coefficients between the different dimensions. The square root of the mean variance extracted for all four dimensions exceeded the correlation coefficient between dimensions. This suggested that there was a distinction between the four dimensions and that the scale demonstrated high discriminant validity (Table 8).

Table 8

Analysis of discriminant validity
Dimensions	Medication Adherence	Self-monitoring Adherence	Rehabilitation Adherence	Life behaviors change Adherence
Medication Adherence	0.822
Self-monitoring Adherence	0.563***	0.784
Rehabilitation Adherence	0.133**	0.322***	0.782
Life behaviors change Adherence	0.040	0.101*	0.410***	0.807
p<0.05;p<0.01; **p<0.001;

Questionnaire reliability analysis

The study revealed that the Cronbach's alpha coefficients for dimensions A, B, C, and D were 0.936, 0.862, 0.916, and 0.928, respectively. Cronbach's alpha coefficient for the total scale was 0.902. Importantly, all Cronbach's alpha coefficients exceeded the threshold of 0.7, indicating a high level of reliability for measuring stroke adherence. The formal questionnaire demonstrated a high internal consistency, reliability, and stability³² (Table 9).

Table 9

Analysis of Cronbach's alpha coefficient for four dimensions
Dimension	Item	Cronbach’s
Medication Adherence	7	0.936
Self-monitoring Adherence	4	0.862
Rehabilitation Adherence	7	0.916
Life behaviors change Adherence	7	0.928
Population (statistics)	25	0.902

Necessity of Questionnaire Development

The sources of information for assessing adherence can be classified into self-reported and non-self-reported techniques, as per the categorization. Self-report methods encompass several techniques, such as patient questionnaires, face-to-face interviews, medication diaries, and telephone follow-up. On the other hand, non-self-report methods involve blood concentration tests, electronic testing, pill counting methods, and pharmacy medication refill records.³⁰ Each of which has its own merits and drawbacks, and none is regarded as the definitive benchmark. Non-self-reporting methods of monitoring adherence, such as assessing drug concentration in the blood or the presence of drug metabolites in the blood or urine, offer precise and unbiased insights into treatment adherence. However, these methods typically require the use of specialized instruments and equipment, which can be costly and impose additional burdens on both patients and social health insurance³³^,³⁴ Furthermore, these methods may be influenced by individual variations among patients. Self-report methods for monitoring treatment adherence are commonly evaluated using questionnaires. Numerous domestic and international studies on adherence to secondary stroke prevention have employed the creation of a database containing pertinent patient data, which are subsequently self-reported by patients for research purposes.³⁵^,³⁶ The GAS scale and the Morisky questionnaire are examples of self-report questionnaires. Nevertheless, these surveys primarily serve the purpose of assessing patient compliance with treatment. These questionnaires are insufficient to capture the extent to which patients with stroke adhere to out-of-hospital care. Therefore, more efficient monitoring methods are required.

Reliability of Questionnaire Development

The experts involved in this study were specialists in nurse management, Chinese medicine nursing, or stroke nursing, all of whom satisfied the inclusion criteria for the DELPHI expert consultation. Therefore, the findings of this study can be considered genuine and trustworthy. Furthermore, it is worth noting that the response rate for both rounds of expert communication in this study was 100%, which suggests that the experts were extremely motivated to participate. The authority coefficients of the experts in the two rounds were 0.87 and 0.88, both of which were above the threshold of 0.7. This suggests that the experts in this study possessed a high level of authority, and that the correspondence results could be deemed reliable. The design of the Out-of-Hospital Adherence Questionnaire for Stroke Patients adhered to the principles of completeness, objectivity, and feasibility in questionnaire design. The first draft of the questionnaire was developed based on the theory of planned behavior, whereas the second draft was created by incorporating feedback from experts in two rounds of correspondence to ensure the reliability of the questionnaire items. Furthermore, this study employed a five-item analytic method to screen entries to ensure the sensitivity, representativeness, and certainty of data. The reliability and validity of the questionnaire were assessed using both a small sample and formal surveys. The questionnaire was prepared scientifically and logically. The literature review is comprehensive and thorough. The experts involved in this study were highly authoritative. The sample size used in the survey was appropriate and sufficient. Statistical analysis was conducted with a high level of rigor.

Limitations of Questionnaire Development

This study had several limitations. The reliability and validity of the questionnaire were established using data from the Shanghai stroke population. Hence, the generalizability of the results to the overall Chinese population cannot be assured. Furthermore, the sample size of 290 participants may be considered insufficient. However, employing a questionnaire to assess out-of-hospital adherence in patients with stroke is currently the best approach. The research group intended to regularly revise the questionnaire at intervals of approximately 3–5 to years. Additionally, we aimed to broaden the scope of the survey by including a larger sample size to enhance its rigor.

In conclusion, the Out-of-Hospital Adherence Questionnaire for Stroke Patients is a reliable and accurate instrument for evaluating stroke patients in routine clinical settings and in population-based research.

Statement of Ethics approval and consent to participate

Ethical principles were considered in all stages of the study. Prior to beginning the study, the aim of the study was explained to the individuals who met the inclusion criteria of the study, and written consent from all patients who agreed to participate was obtained using a voluntary informed consent form, which clearly stated that participation in the study was voluntary and that each participant retained the right to refuse to participate in the study or leave at any time. This trial was approved by the Institutional Ethics Committee of the Shanghai Municipal Hospital of TCM (IRB; reference number 2020SHL-KY-16; IRB at the Shanghai Municipal Hospital of TCM Ethics Committee).

Statement of Consent for publication

Jianping Lu and Hui-jun Sun designed this study. Wu and Qu collected data. Hui-jun Sun and Meiting Wu analyzed the data. Hui-jun Sun and Meiting Wu prepared this manuscript. We confirm that all the listed authors meet the authorship criteria and that all the authors agree with the content of the manuscript had been submitted and agree to be accountable for all aspects of the work.

Statement of Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Statement of Competing interests

The authors have no conflicts of interest to declare.

Funding Sources

This study was supported by the Shanghai Three-Year Action Plan for Promoting Clinical Skills and Clinical Innovation Capabilities in Municipal Hospitals, China

(SHCD2020CR2098B).

Acknowledgements

The authors are grateful to Professor Cui Di Zhang (Dean, School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, China) for supporting our expert consultations. The authors are also grateful to all participants and experts.

Author Contribution declaration

Jianping Lu and Hui-jun Sun designed this study. Wu and Qu collected data. Hui-jun Sun and Meiting Wu analyzed the data. Hui-jun Sun and Meiting Wu prepared this manuscript. We confirm that all the listed authors meet the authorship criteria and that all the authors agree with the content of the manuscript had been submitted and agree to be accountable for all aspects of the work.

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No competing interests reported.

Development and Validation of the Out-of-Hospital Adherence Questionnaire for Stroke Patients

Status:

Version 1

Abstract

Figures

Introduction

Materials and Methods

Establishment of a questionnaire development working group

Conceptual framework and Main concepts

Determination of the content of the questionnaire items

Experts’ consultation

Validation

Statistical analysis

Results

Questionnaire population validation analysis

Questionnaire discrimination and homogeneity analysis

Questionnaire validity analysis

Questionnaire reliability analysis

Discussion

Conclusion

Declarations

References

Additional Declarations

Status:

Version 1