Introduction: Patient decision aid (PDA) is a tool to prompt shared decision-making. The aim of this study was to evaluate the impact of a PDA on Chinese primary open-angle glaucoma patients. Methods: All subjects were randomized into control and PDA group. The questionnaires, including 1) glaucoma knowledge; 2) 8-item Morisky medication adherence scale (MMAS-8); 3) 10-item glaucoma medication adherence self-efficacy scale (GMASES-10); and 4) 16-item decision conflict scale (DCS), were evaluated at baseline, 3- and 6-month follow-up. Results: Totally, 156 subjects participated in this study, including 77 in the control group and 79 in the PDA group. Compared to the control group, PDA group showed around 1 point more improvement in disease knowledge at both 3 and 6 months (both p < 0.05), 2.5 (95% CI: [1.0, 4.1]) and 1.9 (95% CI: [0.2, 3.7]) points more improvement in GMASES-10 at 3 and 6 months, respectively, and reduction in DCS by 8.8 (95% CI: [4.6, 12.9]) points more at 3 months and 13.5 (95% CI: [8.9, 18.0]) points more at 6 months. No difference was detected in MMAS-8. Conclusion: PDA led to improvement in disease knowledge and self-confidence in medication adherence and reduced decision conflict compared to control group for at least 6 months.

© 2023 The Author(s). Published by S. Karger AG, Basel

Introduction

In the past, clinicians tended to have a leading role in disease management, and they commonly give instructions to patients to follow without considering patients’ preferences and values. The choice of treatment depends primarily on clinicians’ preferences. However, what the clinicians perceive the best may not best suit the patients’ needs. Taking an example in glaucoma treatment, while eye drops may be the first choice for many clinicians, some patients may find it difficult to adhere to the regimen or they may experience side effects from the treatment, resulting in poor prognosis. Nonetheless, patients may not be able to discuss with the clinicians for other treatment options, such as laser and surgery, if they do not have sufficient medical knowledge. Shared decision-making (SDM), which emphasizes patient autonomy, informed consent, and patient empowerment, is becoming increasingly important. Patient decision aid (PDA) is a tool to promote SDM and resolve decision conflict. PDA can be used when there are more than one treatment options, when no option has a clear advantage in terms of health outcomes, and when each option has benefits and harms that patients may value differently [1].

PDA has been shown to improve patients’ knowledge, understand their options, and develop a more accurate and realistic expectation of possible benefits and harms [2]. It has also been shown to improve medication adherence, patient value-decision concordance, and encourage active participation in decision-making which some authors postulate may lead to a reduction in medical litigation costs [3–9]. The use of PDA has been adapted to chronic diseases, such as diabetes mellitus, psoriasis, menorrhagia, and osteoarthritis [3, 7, 8, 10]. This suggests that SDM and PDA may be particularly suitable in chronic illness, where outcomes for the various treatment options may be uncertain, thus offering a wider scope for patient autonomy.

In Hong Kong, glaucoma is the leading cause of blindness, accounting for 23% of new registrations of permanent blindness in 2001/2002. The prevalence of primary open-angle glaucoma (POAG) in Asia is approximately 5% [11]. The incidence of glaucoma is known to increase with age. Despite its high prevalence, the knowledge of glaucoma among general public is limited. In a study to investigate the level of knowledge of eye diseases in the Hong Kong Chinese population, only 10.2% could describe glaucoma symptoms correctly, 1.1% described either the anatomy or physiology correctly, and 9.6% were able to mention either surgery, laser or drugs as a form of treatment [12].

Given the high prevalence, chronic nature, and presence of multiple treatment options for POAG, we believe the use of PDA in this group of patients would be beneficial. The treatment options available for POAG patients include medications (eye drops), laser (selective laser trabeculoplasty), and surgery. All of these treatment options were aim to reduce intraocular pressure (IOP) and have specific pros and cons. While medications are usually preferred in Hong Kong, many studies in Western countries show that laser and surgery may be more cost-effective in the long run. As all POAG patients have at least one viable treatment option, these patients will be our target study group. We have developed a PDA according to the International Patient Decision Aid Standards (IPDAS) Collaboration for our POAG patients [13]. Our pilot study showed that glaucoma knowledge, medication adherence, and decision conflict improved with PDA up to 4 weeks [13]. In the current study, we compared the use of PDA with the control group to evaluate its efficacy among glaucoma patients and followed them up for 6 months.

MethodsStudy Design

This study is a mono-center randomized controlled trial (RCT). The eligible subjects were randomized into treatment (PDA) group and control group. Subjects in the PDA group were given a copy of our Chinese POAG PDA, which was developed by our team [13]. The contents were briefly covered in a 5-min briefing conducted by our research assistant. Subjects were then instructed to read through the PDA at home. The PDA for Chinese POAG patients was developed as described.

Sample Size Estimation

The Decision Conflict Scale (DCS) has been used as a primary outcome measure in many RCTs evaluating PDAs [4]. The range of subjects recruited into intervention and control arm ranged from 50 to 200 subjects, with a mean of 92 subjects. In this study, the sample size was calculated based on our pilot study on 65 subjects. In this pilot study, the observed mean (standard deviation [SD]) of DCS at 4-week follow-up was reduced by 14.5 (19.37) from baseline. Assuming the mean (SD) on change from baseline score for control group is −5.0 (19.37). A sample size of 70 per group (total number = 140) will achieve 80% power to reject the null hypothesis of equal mean between the treatment group and the control group. The calculation is using a two-sided two-sample equal-variance t test with a significant level of 0.05. Assuming 10% dropout rate, we will enroll at least 160 subjects into the study to ensure 70 completes for each group.

Randomization

The simple randomization was performed by using random-number generated by Excel (Microsoft Corp., Redmond, WA, USA). In the first column, we insert “PDA” into cells from cell 1 to cell 100 and “CON” into cell 101 to cell 200. In the second column, the Excel RAND function was used to generate 160 random numbers ranging from 0 to 1. Afterward, those random numbers were sorted from the smallest to the largest and sequenced with continuous integers from 1 to 160. The randomization was conducted before the start of the subject recruitment. This study is open-label. During the process of the subject’s enrollment, the enrolled subject was assigned to either PDA or control according to the preset groups.

Subjects Recruitment

Consecutive patients were recruited from the outpatient glaucoma clinic of Lo Fong Shiu Po Eye Centre, Grantham Hospital (teaching hospital of the University of Hong Kong). The inclusion and exclusion criteria were listed below. Patients who fit our recruitment criteria were invited to participate in the study. Informed consent was obtained from all subjects.

Inclusion criteria:

• POAG patients requiring at least one topical medication

• Chinese patients that could speak Cantonese

• Literate patients (for Chinese)

• Adult patients aged ≥ 18

Exclusion criteria:

• Patients who received prior SLT and/or glaucoma surgeries

• Patients who could not read the PDA (including poor vision and illiterate patients (for Chinese))

• Patients who had difficulty understanding purpose of the study

Primary MeasurementsDisease Knowledge

The 16-item disease knowledge questionnaire was adopted from two high quality and validated glaucoma questionnaires [14, 15], mostly from the National Eye Health Education Program questionnaire, which has been evaluated most useful qualitatively and quantitatively for assessing general glaucoma knowledge [15]. The right answer was marked 1 and the wrong or unknown answer was marked 0.

Medication Adherence

Self-reported medication adherence was evaluated by the 8-item Morisky medication adherence scale (MMAS-8) [16–18]. The MMAS-8 has been translated into Chinese version and has been proven to be a reliable and valid tool in medication adherence assessment in epilepsy and type 2 diabetes mellitus in Chinese population [19–21]. The MMAS-8 contains 8 items. The total score of MMAS-8 ranges from 0 to 8, with three categorical Likert scales: low adherence (<6), medium adherence (6 to <8), and high adherence (8).

In addition to self-reported medication adherence, patients’ self-confidence in overcoming barriers to medication adherence was also evaluated using the 10-item glaucoma medication adherence self-efficacy scale (GMASS-10). The GMASS-10 was translated into traditional Chinese by two bilingual researchers. The forward and back translation was performed till the translated version was similar to the original version. For GMASS-10, there were five possible response choices for the self-efficacy items, including very confident, confident, neutral, unconfident, and very unconfident. Each question utilized a scale from 1 to 5, with 1 indicating very confident and 5 indicating very unconfident. Thus, a total score of 10 indicates that they are the most confident to adhere to the medications prescribed, while 50 indicates the worst.

Decision Conflict

The DCS has been shown to correlates with knowledge, regret, and discontinuance and has the ability to differentiate between those who make and delay decisions [22]. In this study, the decision conflict was measured with the Chinese version of the 16-item DCS which has been shown to be valid in assessment of decisional conflict in Chinese population in Hong Kong [23]. The items are given a score of “0” for “yes,” “1” for “probably yes,” “2” for “unsure,” “3” for “probably no,” “4” for “no.” The total score is calculated by summing the 16 items, dividing by 16, and then multiplying by 25. The subscores in the field of informed, values clarity, support, uncertainty, effective decision are calculated from items 1–3, 4–6, 7–9, 10–12, 13–16, respectively, by summing those 3 or 4 items, dividing by the numbers of items, and then multiplying by 25. A score of 0 indicates no decision conflict while 100 indicates the extremely high decision conflict. Scores lower than 25 indicate low decision conflict while those higher than 37.5 are associated with decisional delay or uncertainty [22].

The questionnaires were conducted using a face-to-face mode, evaluated at baseline, and repeated at 3- and 6-month follow-up to determine changes in disease knowledge, medication adherence, and decision conflict. The survey was scheduled based on the patients’ outpatient appointments. Due to the COVID-19 pandemic, patients who cancelled their appointments would miss their follow-up.

Statistical Analysis

Modified intention-to-treat analysis was applied for data analysis in this study [24]. One patient in PDA and 3 patients in control group were excluded due to the loss of follow-up at both 3 and 6 months timepoints. Multiple imputations were used to refill the missing values. Five iterated datasheets were generated. Those 5 datasheets were then merged into a single datasheet using the “bar procedure” [25].

The data were presented in the form of mean and standard deviation (SD) and analyzed using SPSS (Version 27.0.0.0, IBM Corporation, USA). χ2 test was performed to compare the sample distribution and the independent samples t test was performed to compare the mean values between two groups at baseline. The primary outcome of the study is change from baseline in disease knowledge, medication adherence, and DCS scores. The changes were calculated by values at 3- or 6-month follow-up minus values at baseline. The difference in changes between the two groups was analyzed with one-way analysis of covariance (ANCOVA), fitting the baseline data as a covariate. The estimates on the mean of group difference and corresponding 95% confidence intervals (95% [CI]) were reported. A p value <0.05 was considered as statistically significant.

Results

One hundred and sixty subjects were recruited at baseline. Four of them were excluded from analysis due to loss of follow-up at both 3 and 6 months timepoints. The summary to recruitment and follow-up attrition rates are shown in Figure 1. At the end, 156 subjects were included in the study, 77 in control group (72 at 3 months and 77 at 6 months) and 79 in PDA group (60 at 3 months and 73 at 6 months). The reason for loss of follow-up was the cancellation of clinic appointments due to COVID-19 pandemic. The mean age of all enrolled subjects was 59.3 ± 9.5 years, ranging from 25 to 82 years old. The demographic and clinical data of the subjects at baseline are summarized in Table 1. No statistically significant difference was found in either demographic or questionnaire values between the control and PDA groups at baseline.

Fig. 1.

Summary to participants’ recruitment and follow-up.

Table 1.

The demographic and clinical data of all recruited subjects at baseline

CONPDAt*/χ2 ap valueAge (mean ± SD)59±9.959.5±9.4−0.4*0.77Gender (F/M)32/4536/430.1a0.71aPeriod of glaucoma, years7.2±6.17.9±7.2−0.51*0.61Disease knowledge10.3±2.610.2±2.90.25*0.80MMAS-86.5±1.56.2±1.51.1*0.25GMASES-1022.3±7.022.8±6.5−0.37*0.71DCS Total score40.8±1745.3±18.4−1.6*0.11 Informed subscore49.4±22.354.5±22.7−1.7*0.1 Values clarity subscore42.2±25.548±23.3−1.7*0.1 Support subscore33.8±18.238.3±20.3−1.5*0.14 Uncertainty subscore43.4±22.147.8±22−1.4*0.18 Effective decision subscore36.5±17.738.2±19.9−0.7*0.54

The score of glaucoma knowledge was 10.9 ± 2.5 in control group and 12.0 ± 2.3 in PDA group at 3-month follow-up and 11.1 ± 2.6 in control group and 11.9 ± 1.7 in PDA group at 6-month follow-up. Among all the questions, Q12 got the lowest accuracy rate at baseline, only 5.8% of the subjects knew that long-term use of glaucoma eye drops would affect surgery success rate and only 15% changed their mind after using PDA for 6 months. After adjusting with baseline value, the improvement of disease knowledge in PDA group was 1.15 (95% CI: [0.5, 1.8]) more than that in control group at 3 months (F = 12.6, p = 0.001) and 0.9 (95% CI: [0.3, 1.5]) more than that in control group at 6 months (F = 9.8, p = 0.02). The correct answer fill rate of each question (Q) is shown in Table 2. The patients did best for Q3, Q6, Q10, and Q11, with an accuracy rate more than 85% in those items. The PDA increases the accuracy rate by more than 10% in Q1, Q12, Q13, Q14, and Q16.

Table 2.

Patients, responses to the questions of glaucoma knowledge

The questions on glaucoma knowledgeCorrect answerAccuracy ratebaseline, %3 months, %6 months, %Q1. Glaucoma is more common in Asians than in whitesYes36.556.952.7Q2. Glaucoma tends to run in familiesYes71.276.773.6Q3. A person can have glaucoma and not know itYes96.296.998.6Q4. People over age 60 are more likely to get glaucomaYes51.956.260.1Q5. Eye pain is often a symptom of glaucomaNo56.458.559.5Q6. Glaucoma can be controlledYes92.394.697.3Q7. Glaucoma is caused by increased eye pressureYes83.388.485.8Q8. Vision lost from glaucoma can be restoredNo80.883.887.2Q9. A complete glaucoma exam consists only of measuring eye pressureNo54.863.056.8Q10. Treatment for glaucoma is lifelongYes86.591.389.9Q11. If I am in a hurry, I can apply all glaucoma eye drops in one goNo93.695.398.0Q12. Long-term use of glaucoma eye drops affects surgery success rateYes5.824.618.2Q13. SLT laser is effective in all glaucoma patientsNo53.270.068.2Q14. SLT laser is safe with relatively few side effectsYes73.789.291.2Q15. After a successful glaucoma surgery, my eyes will see betterNo42.351.552.0Q16. After a successful glaucoma surgery, my glaucoma is cured for lifeNo50.060.858.8

The score of MMAQ-8 was 6.3 ± 1.3 in control group and 6.4 ± 1.5 in PDA group at 3 months and 6.6 ± 1.4 in control group and 6.4 ± 1.6 in PDA group at 6 months. The score of GMASES-10 was 23.3 ± 6.1 in control group and 20.1 ± 6.6 in PDA group at 3-month follow-up and 22.6 ± 7.0 in control group and 20.9 ± 6.7 in PDA group at 6-month follow-up. As shown in Table 3, after adjusting with baseline value, the improvement of self-confidence in medication adherence measured by GMASES-10 was significantly higher in the PDA than in the control group at both 3- and 6-month follow-up. However, the difference in the improvement of medication adherence measured by 8-item MMAQ was not significant between the two groups.

Table 3.

Changes of medication adherence scores at the 3- and 6-month follow-up

Medication adherenceCONPDADifferenceFap valueMMAS-8 [mean (95% CI)]* Changes from baseline at 3 months−0.1 (−0.3, 0.1)0.1 (−0.1, 0.4)0.3 (−0.1, 0.6)2.40.12 Changes from baseline at 6 months0.2 (−0.1, 0.5)0.1 (−0.2, 0.4)−0.1 (−0.5, 0.3)0.10.75GMASES-10 [mean (95% CI)]* Changes from baseline at 3 months0.9 (−0.2, 2.0)−1.6 (−2.7, −0.5)−2.5 (−4.1, −1.0)10.10.02 Changes from baseline at 6 months0.2 (−1.0, 1.5)−1.7 (−2.9, −0.5)−1.9 (−3.7, −0.2)4.80.03

The total DCS score was 37.0 ± 16.0 in control group and 30.2 ± 13.9 in PDA group at 3 months and 37.4 ± 17.5 in control group and 25.6 ± 13.3 in PDA group at 6 months. The subscores of informed, values clarity, support, uncertainty, and effective decision were 42.4 ± 19.7, 35.4 ± 20.2, 33.0 ± 16.0, 39.7 ± 20.8, and 35.4 ± 17.2 in control group and 42.7 ± 22.2, 38.8 ± 24.1, 33.5 ± 17.5, 39.4 ± 19.5, and 33.8 ± 18.4 in PDA group at 3-month follow-up and 33.2 ± 17.1, 27.9 ± 16.0, 26.6 ± 14.7, 34.1 ± 18.7, and 29.3 ± 15.1 in control group and 27.0 ± 17.1, 23.3 ± 16.3, 25.1 ± 15.0, 39.4 ± 19.5, and 27.6 ± 16.0 in PDA group at 6-month follow-up, respectively. After adjusting with the baseline DCS value (Table 4), the reduction in decision conflict measured by DCS was significantly higher in the PDA than the control group at both 3- and 6-month follow-up.

Table 4.

Changes of DCS scores at the 3- and 6-month follow-up

DCSCONPDADifferenceFap valueChanges from baseline at 3-month follow-up [mean (95% CI)]* Total score−5.1 (−8.0∼−2.1)−13.9 (−16.8, −11.0)−8.8 (−12.9, −4.6)17.40.000 Informed subscore−8.9 (−12.6, −5.1)−20.3 (−24.0, −16.6)−11.4 (−16.7, −6.1)18.30.000 Values clarity subscore−9.2 (−13.1, −5.4)−18.5 (−22.3, −14.7)−9.3 (−14.7, −3.9)11.40.001 Support subscore−2.6 (−6.0, 0.7)−10.0 (−13.3, −6.7)−7.4 (−12.1, −2.7)9.60.002 Uncertainty subscore−5.1 (−9.0, −1.2)−12.8 (−16.6, −9.0)−7.7 (−13.2, −2.2)7.70.006 Effective decision subscore−1.7 (−4.7, 1.4)−8.6 (−11.6, −5.5)−6.9 (−11.3, −2.6)9.80.002Changes from baseline at 6-month follow-up [mean (95% CI)]* Total score−4.6 (−7.8∼−1.3)−18.3 (−21.4∼−15.2)−13.5 (−18.0, −8.9)36.00.000 Informed subscore−8.4 (−12.5, −4.4)−26.4 (−30.4, −22.5)−18.0 (−23.7, −12.3)39.00.000 Values clarity subscore−5.7 (−10.0, −1.4)−23.2 (−27.5, −18.9)−17.5 (−23.6, −11.5)32.10.000 Support subscore−2.1 (−5.7, 1.5)−11.5 (−15.1, −7.9)−9.4 (−14.5, −4.3)13.50.000 Uncertainty subscore−5.8 (−9.5, −2.0)−18.9 (−22.6, −15.2)−13.1 (−18.4, −7.8)23.80.000 Effective decision subscore−3.4 (−6.8, −0.01)−12.5 (−15.9, −9.2)−9.1 (−13.9, −4.4)14.40.000Discussion

Glaucoma is a chronic disease which requires long-term commitment of both the patients and the doctors. Traditionally, the management decision was predominated by the doctors, which now we foresee a change in such practice. Doctors should try to engage patients more on the co-management of chronic disease. Our PDA showed that patients had suboptimal disease knowledge (scored around 10 points out of 16 questions in both groups). There was improvement in disease knowledge of around 1 point better than that in the control group. Although this is statistically significant, such small improvement may not be clinically significant. The PDA contains general information related to disease knowledge, including the prevalence of glaucoma, the difference between glaucoma and cataract in causing visual disturbance, as well as what primary glaucoma and open-angle glaucoma are. However, it does not provide all the answers to those 16 questions listed in the questionnaire. In addition, for some of the questions, the answers cannot be directly found in the PDA. For example, the PDA mentioned that glaucoma treatment can only reduce IOP to prevent the progression of vision loss and the vision would fluctuate after the surgery but did not point out how surgery may affect the vision. Moreover, some patients may not read through the entire PDA components which they think may not be relevant to them. For Q12, although the PDA contains the direct answer, only around 15% patients in the PDA group could answer correctly. This question might be a bit difficult to patients without medical background. The answer to this question was shown in a table (side effect of the glaucoma eye drops) in the PDA. However, the PDA did not explain in detail why and how long-term use of eye drops affects the surgery rate. We will advocate more patient education especially on glaucoma treatments and outcomes and deliver in multiple forms, such as lectures or videos so that patients can know more about their disease condition in addition to the PDA given to them. Previous studies have shown that improvement in disease knowledge was associated with better self-management care in chronic obstructive pulmonary disease and chronic renal disease [26, 27]. Therefore, with improvement in glaucoma knowledge, we believe glaucoma patients who may be more motivated in managing their own disease.

Improvement in medication adherence improves disease outcome and reduces wastage of drug [28, 29]. This study also wants to investigate whether PDA can serve as a simple tool to assist the patients to enhance their confidence in applying eye drops and improve their medication adherence. In this study, the self-confidence in medication adherence was moderate in at baseline (scored around 20/50 marks). We observed a significantly better improvement of self-confidence in medication adherence measured by GMASES-10 in the PDA group, which was 2.5 and 1.9 marks better than the control group at 3 and 6 months, respectively. This shows that patients have more confidence in observing the daily routine of applying medications after reading the PDA. The GMASES-10 has been found to be strongly associated with medication adherence evaluated by Medication Event Monitoring System [30]. However, in this study, there seem to be no significant changes in the medication adherence measured by MMAQ-8 after PDA intervention. This may be due to the relatively high baseline value of 6 out of 8 (i.e., patients claimed to be quite adhering to the medication to start with). There may not be much room for improvement. However, this questionnaire is self-reported, so we cannot be sure about the actual adherence of patients. In future studies, we may include subjects with poor medication adherence at baseline, so as to assess how PDA may assist them in improving medication adherence.

The most significant change among the outcome measures was DCS. This shows that PDA can effectively help patients make a choice confidently which best suits them. PDA helps clear their uncertainty on treatment options and assists them to make an informed decision with consideration on their own values. It is important for clinicians to empower the patients with sufficient knowledge about their diseases and treatment options available, before patients can make a shared decision. Previous studies showed that when patients are involved in decision-making, they will be more compliant to the treatment [31, 32]. SDM is also associated with more satisfaction in treatment [33] and can possibly result in less complaints or even medical litigations which are often related to miscommunications between clinicians and patients, although to date there is not yet clear evidence to support this assumption [34].

Our study has several limitations. First, for patients to read and understand the PDA and the questionnaires, they must have a reasonably good vision and cognitive status. PDA may not be applicable in those with too poor vision associated with advanced glaucoma and those with limited cognitive functions. Second, this study only investigated the effect of PDA on decisional conflict but did not test if PDA influences treatment decision. Third, the follow-up period was 6 months and was not able to monitor the effect PDA in halting the progression of glaucomatous optic neuropathy. Fourth, the severity of disease, baseline IOP, side effects of medications, and patients’ preference would affect the patients’ medication adherence and choices of treatment; however, we could not take all these factors into consideration in current study. Furthermore, this study involved patients in a single center. It may not well represent population around the world. In the future, multicentered studies should be carried out to evaluate the efficacy of PDA. Nonetheless, our study is the first randomized control trial to evaluate how PDA can help glaucoma patients in the literature.

To conclude, our study showed that PDA can improve disease knowledge, patients’ confidence in medication adherence and reduce decision conflict in Chinese POAG patients in Hong Kong. We advocate distributing such PDA to patients who may need to make choices among different treatment options. It helps patients make an informed choice taking into consideration of their own values, rather than just following the suggestions made by the clinicians.

Acknowledgments

The MMAS-8 Scale, content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAR, LLC., www.moriskyscale.com.

Statement of Ethics

This study was reviewed and approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster, approval number UW-18148. Written informed consent was obtained from participants prior to enrollment in the study. The study was conducted in adherence to the tenets of Declaration of Helsinki and reported based on Consolidated Standards of Reporting Trials (CONSORT) guideline.

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

Supported by the Health and Medical Research Fund (Grant No. 15161691) by the Research Fund Secretariat, Hong Kong.

Author Contributions

B.N.K. Choy and J.W.H. Shum contributed to the design and implementation of the research; M.M. Zhu contributed to the analysis of the results; M.M. Zhu, B.N.K. Choy, and W.W.T. Lam contributed to the preparation of the manuscript.

Data Availability Statement

Data are not publicly available due to ethical reasons. Further inquiries can be directed to the corresponding author.

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