Keywords

3.1 Background

Depressive disorder (also known as depression) is a common mental disorder that involves a depressed mood or loss of pleasure or interest in activities for long periods of time (World Health Organization, 2023). Different from regular mood changes and feelings about everyday life, depression can impact all aspects of life, such as relationships with family, friends and community (World Health Organization, 2023). It can stem from or result in problems at school or at work.

Depression may afflict anyone, especially those who have experienced abuse, severe losses or other stressful events (World Health Organization, 2023). It is estimated that about 3.8% of the population worldwide suffer from depressive disorder, including around 5% of adults (4% of men and 6% of women), and 5.7% of older adults aged over 60 years (World Health Organization, 2023). About 280 million people worldwide have depression (Institute of Health Metrics and Evaluation, 2023). Women are more likely to develop depression than men: depression is estimated to be about 50% more common among women than among men (World Health Organization, 2023). Over 10% of pregnant women and postpartum women suffer from depression (Woody et al., 2017). Depression can lead to suicide, which claims the life of more than 700,000 people annually and ranks the fourth leading cause of death among those who are aged between 15 and 29 years (World Health Organization, 2023).

Regardless of known, effective treatments of mental illnesses, over 75% of people in low- and middle-income countries are untreated (Evans-Lacko et al., 2018) due to various obstacles to effective care, including a lack of investment in mental health care, a lack of trained healthcare providers and social stigma attached to mental disorders (World Health Organization, 2023).

Depressive disorder stems from the complex interplay between social, physical, psychological, and biological factors (World Health Organization, 2023). Individuals who have experienced adverse life events (e.g., unemployment, bereavement, traumatic events, etc.) are more likely to develop depression, which can, in turn, result in more stress and dysfunction and worsen the affected person’s life situation (World Health Organization, 2023). Many factors that influence depression (e.g., physical inactivity, abuse of alcohol, etc.) are known risk factors for diseases including cardiovascular disease, cancer, diabetes and respiratory diseases, which, in turn, make people experience depression because of the difficulties in managing their condition (World Health Organization, 2023).

Depression can be effectively treated. Effective treatments include psychological treatment and antidepressant medications. Psychological treatments include teaching new ways of thinking, coping with or relating to others, talk therapy with professionals and supervised lay therapists, behavioral activation, cognitive behavioral therapy, interpersonal psychotherapy, and problem-solving therapy (World Health Organization, 2023).

Depression can be effectively reduced through some prevention programs. These programs include school-based programs to enhance a pattern of positive coping in children and adolescents, interventions for parents of children with behavioral problems, exercise programs for older persons, and self-care (World Health Organization, 2023). Self-care can effectively facilitate managing depression symptoms and promoting overall well-being (World Health Organization, 2023). It takes on many different forms, including trying to keep doing activities one used to enjoy, exercising regularly, sticking to regular eating and sleeping habits as much as possible, avoiding or cutting down on alcohol and not using illicit drugs, staying connected with friends and family, talking to someone one trusts about one’s feelings, seeking help from a healthcare provider, joining a support group, etc. (World Health Organization, 2023).

WHO’s Mental Health Action Plan 2013–2030 emphasizes the essential steps to provide appropriate interventions for individuals with mental illnesses including depression. Two categories of interventions are highlighted: increasing services for people with mental, neurological and substance use disorders through care provided by health workers, and developing psychological, group-treatment, and cognitive-behavioral intervention manuals (World Health Organization, 2023).

The treatments, prevention programs and interventions above can fall into three types of locus of control: the affected person’s internal motivation, health and medical professionals and other people (e.g., family, friends, those one trusts, etc.). These three types of health locus of control have already been captured in previous studies (Donovan & O’Leary, 1978; Gebhardt et al., 2001; Lewis et al., 1978; Macleod & Macleod, 1998; Martin, 1999; Martin & Jomeen, 2004; Martin et al., 1990; Pastor et al., 1993; Saltzer, 1982; Strudler-Wallston & Wallston, 1978; Wallston et al., 1976). However, the treatments, prevention programs and interventions proposed by World Health Organization (2023) have not involved the affected people’s belief about the influence of chance on the prevention and treatment of depression, which has been proven important for health-related behaviors and health outcomes by Wallston et al (1994). Informed by these studies, we hypothesized that the prevention and treatment of depression could be impacted by four different types of health locus of control measured by the four subscales of the Multidimensional Health Locus of Control Scale (MHLC) Form C, ‘internal,’ ‘chance,’ ‘powerful other people,’ and ‘doctors,’ respectively, which should be investigated to deliver tailor-made education and interventions. Based on this hypothesis, we raised our research questions: how many clusters can the study participants be grouped into based on their attitudes towards and beliefs about the prevention and treatment of depression, specifically their beliefs about the source of reinforcements for health-related behaviors if they develop depression? Can such beliefs be associated with the participants’ demographic features and health literacy status?

Patients’ attitudes towards the conditions from which they are suffering can be measured by the locus of control (LOC) construct, as extensively demonstrated by a huge variety of pathology (Donovan & O’Leary, 1978; Lewis et al., 1978; Saltzer, 1982; Martin et al., 1990; Macleod & Macleod, 1998; Pastor et al., 1993). It had been clinically observed that the LOC construct can mediate health status and outcomes (Gebhardt et al., 2001; Martin, 1999; Martin & Jomeen, 2004; Strudler-Wallston & Wallston, 1978; Wallston et al., 1976), and it has proven helpful in predicting and explaining specific health-related behaviors (Strudler-Wallston & Wallston, 1978). Based on the LOC construct, individuals can be categorized into two main classes: those believing that their health status (or sickness) results from their own behaviors (‘health-internals’) and those considering that their health status is generally determined by factors over which they have poor control, like chance or powerful others (‘health-externals’) (Wallston et al., 1976). Wallston et al. later proved the importance of assessing beliefs in the influence of chance and powerful others separately (Wallston et al., 1978). More recently, Wallston et al. (1994) have shown that it is also helpful to distinguish between expectations related to doctors and those related to significant others (e.g., relatives, friends, etc.) within the ‘powerful others’ construct. Health LOC has been conceptualized as a construct comprising at least 3 dimensions (Wallston et al., 1978). The most extensively used, validated instrument of LOC in health is the Multidimensional Health Locus of Control Scale (MHLC) (Wallston et al., 1978). This measure consists of 18 items that are rated on a 6-point Likert scale ranging from strongly disagree (= 1) to strongly agree (= 6). These 18 items are divided into 3 6-item subscales that measure ‘internal,’ ‘chance,’ and ‘powerful others’ LOC. Higher scores for each subscale indicate greater belief in that subscale domain in relation to health. There are 3 refined versions of the MHLC, namely, the MHLC Form A, the MHLC Form B, and the MHLC Form C (Wallston et al., 1994). The MHLC Form C consists of 4 subscales, ‘internal’ (6 items), ‘chance’ (6 items), ‘powerful other people’ (3 items), and ‘doctors’ (3 items) (Wallston et al., 1978).

The MHLC Form C has been applied to enhance the knowledge about the HIV + patients’ point of view of their complex health condition (Ubbiali et al., 2008), determine how LOC relates to health care use, medication adherence, missed school, and readiness for transition to adult medical care for youths with chronic conditions (Nazareth et al., 2016), explore the relationship between LOC and pregnancy (Green et al., 1990; Lavender et al., 1999; Pang et al., 2001; Scott-Palmer & Skevington, 1981; Tinsley et al., 1993), etc. However, it has never been translated and adapted to Chinese and used exclusively for measuring people’s beliefs about the prevention and treatment of depression in mainland China. In the context that there is no such a scale that has been designed in Chinese for this particular purpose, it is necessary to translate and adapt the MHLC Form C to Chinese for research. Considering that the MHLC Form C is a “general purposes condition-specific locus of control scale that could easily be adapted for use with any medical or health-related condition” (Wallston et al., 1994), we adapted it for use with depression in the questionnaire we designed for our study. We believe that this adapted scale is most likely to solicit patients’ attitudes towards the prevention and treatment of depression, based on which tailor-made education, intervention and treatment could be delivered for the benefit of the prevention and treatment of this disease. However, it has never been used in this respect. Considering the magnitude of depression among people in China, it is imperative to examine patients’ attitudes towards and beliefs about the prevention and treatment of this disease to deliver more targeted education, intervention, prevention and treatment so as to reduce its prevalence and the mortality rate caused by it.

The objective of this study was threefold. First, we aimed to translate and adapt the MHLC Form C to Chinese and make the Chinese version depression specific. And then, we used the depression-specific Chinese version to classify the patient participants into different latent classes according to their attitudes towards and beliefs about the prevention and treatment of depression, and identified significant factors that were closely associated with the low-efficacy cluster to provide essential implications for the delivery of tailored education and interventions and the administering of targeted prevention and treatment.

3.2 Methods

3.2.1 Translation and Adaptation of the MHLC Form C

The symmetrical translation approach was adopted to ensure more accurate adaptation and cross-cultural validation of the Chinese version of the MHLC Form C. This approach is the most recommended methodology due to the top priority it gives to faithfulness of meaning and colloquial expressions in both the source and target languages rather than to word-for-word literal translation (Jones & Kay, 1992). It is the only method that facilitates the comparison of responses provided by individuals from one culture with those given by people from another culture (Jones & Kay, 1992; Jones et al., 2001) and the establishment of the most relevant types of cross-cultural equivalence (semantic, conceptual, content, technical and criterion) (Hilton & Skrutkowski, 2002). Although back-translation was the most commonly used methodology in the translation of mental health materials (Barger et al., 2010), back-translation cannot really ensure equivalence, particularly when many terms associated with mental health are extremely challenging or even impossible to translate directly (Barger et al., 2010). As a result, we used the “decentering” strategy rather than backward translation to increase the likelihood of translation success (Brislin et al., 1973). Decentering enables translators to consider the target and source texts equal in importance by allowing modification of the source text during the process of translation (Brislin et al., 1973). It is designed to facilitate establishing equivalence between the source and target texts. In the decentering process, we not only allowed both the source and target languages to shape decision-making in translation but also allowed the target language and culture to influence the source text (Black, 2018). In the whole translation process, we adhered to the “centering” (Brislin, 1970) principle, which attaches equal importance to both the source (English) language and the target (Chinese) language.

In this chapter, we will go through the steps of the cross-cultural validation of depression scales. These steps, as shown below, “incorporated the most recommended ones in a user-friendly guideline to facilitate adoption, consistency and use” (Sousa & Rojjanasrirat, 2011: 269).

3.2.1.1 Forward Translation of the MHLC Form C into Chinese

The MHLC Form C in the source English language was forward translated to the target Chinese language by two independent translators (Meng Ji and Yi Shan), whose mother language is the desired target Chinese language. These translators are bilingual (i.e., fluent in English and Chinese) and bi-cultural (i.e., having in-depth experience in Chinese and English culture. Both translators are trained in the use of “health care terminology and the content area of the construct” (Sousa & Rojjanasrirat, 2011: 269) of the MHLC Form C in Chinese, and the use of “colloquial phrases, health care slang and jargon, idiomatic expressions, and emotional terms in common use” (Sousa & Rojjanasrirat, 2011: 269). We developed two translated versions using words and sentences that cover both the medical and the usual spoken (colloquial) language with its cultural nuances. After that, we discussed the two versions with three medical professionals (Zhaogang Dong, Zhaoquan Xing, and Xiaofei Xu from Qilu Hospital of Shandong University, China) to minimize inconsistencies potentially introduced by the two independent translators.

3.2.1.2 Comparison of the Two Translated Chinese Versions of the MHLC Form C

A third bilingual and bi-cultural translator (Weiwei Chu) compared not only the instructions, items and responses of the two forward-translated Chinese versions but also the two Chinese versions with the original English version of the MHLC From C to identify “ambiguities and discrepancies of words, sentences and meanings” (Sousa & Rojjanasrirat, 2011: 269). Any potential ambiguities and discrepancies were discussed and resolved through discussions among the research team (Meng Ji, Yi Shan, Weiwei Chu, Zhaogang Dong, Zhaoquan Xing, and Xiaofei Xu). When consensus was reached among all members of the research team, the preliminary initial translated Chinese version of the MHLC From C was generated.

3.2.1.3 Pilot Testing of the Preliminary Initial Translated Chinese Version of the MHLC from C with a Chinese Sample: Cognitive Debriefing

The preliminary initial translated Chinese version of the MHLC From C was pilot tested among native Chinese patient participants to evaluate the instructions, items, responses of the translated instrument for clarity. Since a sample size of 10–40 informants is recommended in previous studies (Beaton et al., 2000; Sousa et al., 2009), we recruited ten volunteers for a cognitive interview, including five women and five men with year 6, year 9, year 12, and university education who were aged 32 to 66 years old. Based on the “think-aloud protocol” (Jääskeliänien, 2010), they were asked to provide open feedback on whether and how they understood the questionnaire while “thinking aloud” (Zeugfang, 2018). This step aimed to test the comprehensibility of the preliminary initial translated Chinese version of the MHLC From C. Subsequently, the 10 volunteers and all researchers of this study (Meng Ji, Yi Shan, Weiwei Chu, Zhaogang Dong, Zhaoquan Xing, and Xiaofei Xu) resolved problems with the question organization, the instrument layout (including the font size), and elusive questions or concepts (Barros et al., 2022). We focused on challenging questions and concepts related primarily to cultural relevance (whether they were relevant to the participants’ daily life) and linguistic accessibility (whether they were comprehensible or ambiguous to the participants) (Shan & Ji, 2023). This step ensured the face validity (Shan & Ji, 2023) and the conceptual, semantic and content equivalence (Sousa & Rojjanasrirat, 2011), and further allowed the structure of sentences used in the translated Chinese tool to be easily understood by the target patient population before psychometric testing (Sousa & Rojjanasrirat, 2011).

3.2.2 Using the Chinese MHLC Form C to Classify Patients and Identifying Factors Associated with Low Self-efficacy

3.2.2.1 Questionnaire Design

We designed a five-section questionnaire, including (1) Section 1: age, gender, education, and self-reported disease knowledge, (2) Section 2: the Chinese version of the All Aspects of Health Literacy Scale (AAHLS) (https://healthliteracy.bu.edu/documents/34/AAHLS%20Tool.pdf; Chinn & McCarthy, 2013), (3) Section 3: the Chinese version of the eHealth Literacy Scale (eHEALS) (Koo et al., 2012), (4) Section 4: the Chinese version of the General Health Numeracy Test (GHNT-6) (https://healthliteracy.bu.edu/documents/36/GHNT_6%20.pdf; Shan et al., 2023a, 2023b), and (5) Section 5: the translated and adapted Chinese version of the Multidimensional Health Locus of Control Scale (MHLC) Form C (Wallston et al., 1994). Literacy in health information is becoming a critical factor that is essential for health status (Berkman et al., 2011). The ASHLS consists of three sub-scales, functional, communicative, and critical, which play different roles (Chinn & McCarthy, 2013; Nutbeam, 2000; Shan et al., 2023a, 2023b). The functional health literacy (FHL) sub-scale contains 3 related questions regarding one’s ability to comprehend health information (FHL1), seek help (FHL2), and complete formal documents (FHL3) (Nutbeam, 2000). The sum of the FHL sub-scale increases with one’s functional health literacy, as higher FHL sum scores are indicative of greater capability to independently comprehend health materials, complete official documents, and effectively obtain help from others (Shan et al., 2023a, 2023b). Communicative health literacy (COHL) comprises two components: information gathering and processing skills, and interactive skills essential for successful consultations with health providers (Chinn & McCarthy, 2013; Nutbeam, 2000). Higher COHL sum scores are indicative of lower COHL (Shan et al., 2023a, 2023b). The critical health literacy (CRHL) sub-scale of the AAHLS assesses one’s ability to evaluate the quality of health materials consciously, critically, purposefully from various sources including internet, one’s engagement with health professionals, and acting at both individual and community levels. Chinn and McCarthy (Chinn & McCarthy, 2013) investigated the relationship between the total AAHLS score and the sub-scale scores with sex, ethnicity, and reported presence of a long-term health condition. The 8-item eHEALS evaluates the study participants’ knowledge and skills that are essential for using eHealth resources and interventions (Koo et al., 2012).

The GHNT has 6 related questions about one’s ability to comprehend and utilize simple quantitative health materials. As a result, a higher sum score of the GHNT indicates lower general health numeracy skills (Shan et al., 2023a, 2023b). The 18-item MHLC Form C comprises 4 subscales that measure ‘Internal,’ ‘Chance,’ ‘Doctor,’ and ‘Powerful Others’ locus of control, that is, beliefs that the source of reinforcements for health-related behaviors is primarily internal, a matter of chance, or under the control of doctors or powerful others (Wallston et al., 1994). Such beliefs can motivate health behavior, which refers to taking voluntary actions to promote health, reduce health risks (Sarafino, 2006), and mediate health status (Jomeen & Martin, 2002). Individuals categorized as having an ‘Internal’ locus of control are more likely to engage in health behaviors and are more knowledgeable regarding their health problems (Bane et al., 2006; Takaki and Yano 2006). Considering that the MHLC Form C is a “general purposes condition-specific locus of control scale that could easily be adapted for use with any medical or health-related condition” (Wallston et al., 1994), we adapted it for use with depression in the questionnaire. Informed by relevant studies (Martin, 1999; Berkman et al., 2011; Sarafino, 2006; Jomeen & Martin, 2002; Bane et al., 2006; Takaki & Yano, 2006), we hypothesized that the participants’ status of health belief and self-confidence measured by the MHLC Form C in Section 5 could be closely associated with information collected through Sections 1–4.

3.2.2.2 Participant Recruitment and Questionnaire Survey

The study participants were recruited from Qilu Hospital of Shandong University, China, using randomized sampling. Participants who had met four predefined inclusion criteria were invited to participate in this survey: (1) being aged ≥ 18 years, (2) having at least primary education (Year 6 schooling) to understand the questions in the questionnaire, (3) being patients rather than relatives accompanying patients, and (4) participating in the survey voluntarily. We made face-to-face contact with Mandarin Chinese-speaking patients who were attending the outpatient clinic and those who were hospitalized to identify those who satisfied the inclusion criteria, explain to them about the purpose of the survey, and ask them to participate in the web-based survey as scheduled. We identified 1208 eligible patients.

The survey lasted one month from July 20, 2022, to August 19, 2022. The questionnaire was administered via wenjuanxing (https://www.wjx.cn/ [accessed 2022-07-21]), the most popular web-based questionnaire platform in China. Participants filled out the administered questionnaire on the web. Returned questionnaires were considered valid only when all question items included were answered according to our predefined validation criterion. On August 20, 2022, the returned questionnaires were downloaded in the format of an Excel file (Microsoft Corp) from wenjuanxing. A total of 988 answered questionnaires were returned, with a response rate of 81.8% (988/1208). We double-checked the returned questionnaires and found all of them to be valid.

3.2.2.3 Data Collection, Coding and Analysis

On August 20, 2022, the answered questionnaires were downloaded in the format of an EXCEL file from wenjuanxing. We double checked the validity of the returned questionnaires before coding valid data using the predefined coding schemes based on Likert scales with varying score ranges for different questionnaire items. After that, we used latent class modelling (LCA; Latent GOLD 5.0) to classify the patient participants into different clusters according to the their status of health attitudes and belief measured by the translated Chinese version of the MHLC Form C which had been made depression-specific, and identified factors significantly associated with the low-efficacy cluster.

LCA is increasingly applied in social and health sciences. LCA has methodological advantages over traditional clustering techniques (Nylund-Gibso & Choi, 2018; Tein, 2013; Morovati, 2014; Morgan, 2014). A notable benefit of LCA is the probabilistic attribution of latent class membership to study participants using maximum likelihood estimation (Nylund-Gibso & Choi, 2018). As a result, each observed participant attains a probability of belonging to a certain latent class. For example, within a 2-class LCA solution, a study participant can have 2 probabilities associated with either latent class. The combined probabilities of class memberships sum to 1, based on the conditional independence assumption of LCA. The probabilistic nature of LCA adds to the complexity of the result interpretation. However, in practice, the more flexible, intuitive approach of LCA when compared with “hard, rigid” clustering techniques allows researchers more insights into the impact of predictor variables on latent class membership fluidity and dynamics, as well as the susceptibility of class memberships to the definition and selection of probability thresholds to suit different research purposes.

3.2.2.4 Ethics Approval

This study was approved by the Ethics Review Board of Qilu Hospital of Shandong University, China. The review number is KYLL-202208-026. The study data were anonymized to protect the privacy and confidentiality of the study participants. Because the participants voluntarily participated in the survey to support and promote academic research, no compensation was provided for them as per the common practice in China.

3.3 Results

3.3.1 Translation and Adaptation of the MHLC Form C

3.3.1.1 Forward Translation of the MHLC Form C into Chinese

Two translated versions were produced independently by two translators using words and sentences that cover both medical and usual spoken (colloquial) language with its cultural nuances. Table 3.1 was translated by Yi Shan, and Table 3.2 was translated by Meng Ji.

Table 3.1 Chinese Version 1 of the MHLC Form C
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Table 3.2 Chinese Version 2 of the MHLC Form C
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When discussing these two versions with Zhaogang Dong, Zhaoquan Xing, and Xiaofei Xu from Qilu Hospital of Shandong University, we did not identify idiosyncrasies that had been introduced by the two independent translators. These two versions were then subjected to further analysis in Sects. 4.3.1.2 and 4.3.1.3.

3.3.1.2 Comparison of the Two Translated Chinese Versions of the MHLC Form C

The third bilingual and bi-cultural translator (Weiwei Chu) compared the two translated Chinese versions and checked these two Chinese versions against the original English version. It was found that although these two versions were largely semantically equivalent to the original English version, some discrepancies of words and sentences between the two Chinese versions were identified in terms of Items 3, 10, 11, 13, 15, and 18, as has been marked with bold font in Tables 3.1 and 3.2. To make comparison convenient, these items from both tables are presented in Table 3.3.

Table 3.3 Comparison of translated Versions 1 and 2 with the original English version of the MHLC Form C
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As can be seen from Table 3.3, Versions 1 and 2 showed different degrees of adaptation in which the wording and sentence structures have been adjusted to produce colloquial and idiomatic translated items that are more likely to be culturally relevant, comprehensible, and acceptable to Chinese readers. Some problems were found in these two translated versions. As the third translator pointed out, the wording and sentence structures of some translated items needed to be modified to make them more linguistically and culturally appropriate or adapted although the translated versions were largely understandable. In other words, the translated versions needed to be revised in terms of colloquial and idiomatic expressions that were more culturally relevant, understandable, and acceptable by means of various translation techniques including addition and deletion, literal and liberal translation, recasting, and so on. To this end, the research team (Meng Ji, Yi Shan, Weiwei Chu, Zhaogang Dong, Zhaoquan Xing, and Xiaofei Xu) discussed any potential ambiguities and discrepancies round after round until consensuses were reached among all team members. The results of discussion are presented item after item in the following paragraphs.

First, “see my doctor” in Item 3 was translated into “去找医生治疗” (“visit a doctor for treatment”) and “看医生” (“see a doctor”) in Version 1 and Version 2 respectively, but these two Chinese translations were changed to “看病” (“treat my disease”) which was considered as more habitually used by and more culturally relevant to Chinese populations in their daily life. By contrast, “看医生” (“see a doctor”), though understandable to Chinese people, is less culturally relevant and acceptable in the Chinese context, due to the fact that people usually do not have their private doctor but go to hospital to visit a doctor for treatment if they are ill. “去找医生治疗” (“visit a doctor for treatment”), although understandable, is less colloquial and idiomatic compared with “看病” (“treat my disease”) which is the most used expression among Chinese people. The Chinese translations of “am less likely to have problems with” in Item 3, “病情就不太可能出现问题” (“problems are less likely to occur to my condition”) in Version 1 and “症状就会少出些问题” (“less problems are likely to occur to my symptoms”) in Version 2, were changed to “就不大会出问题” (“am less likely to have problems”) for more colloquial and idiomatic expression and thus for greater acceptability to Chinese readers based on their lived experiences.

In the translation of Item 10, “is up to” and “to see” was combined into “必须确保” (“must ensure”) in Version 1 and “要确保” (“need to ensure”) in Version 2, and “that the right things happen” was translated and adapted to “不出差错” (“there are no slips”) in Version 1 and “不犯错误” (“no mistakes are made”) in Version 2. After discussion, we decided to change these adapted translations to “做该做的事情” As a result, the whole item, “In order for my depression to improve, it is up to other people to see that the right things happen.” was revised to “要让我的抑郁症好转, 其他人要为我做该做的事情。” (“In order to improve my depression, other people need to do the right things for me.”), which was more semantically equivalent on the one hand and more culturally understandable and acceptable on the other hand.

In Item 11, “Whatever improvement” was translated into “什么程度的改善” (“To what extent (my depression) is improved”) in Version 1 and “多多少少有了好转” (“more or less improvement”) in Version 2, and “is largely a matter of good fortune” was translated into “很大程度上都纯属幸运” (“is largely a sheer matter of luck”) in Version 1 and “那都是我走运” (“is completely attributable to my luck”) in Version 2. To achieve better semantic equivalence, we decided to revise the Chinese wordings here to “我的抑郁症改善多少, 主要看我运气好坏。” (“Whatever improvement occurs to my depression is mainly up to my luck.”), which was believed to more cater to habitual wordings and to be more easily accepted in the Chinese cultural settings.

Item 13, “I deserve the credit when my depression improves and the blame when it gets worse.”, was translated into “我的抑郁症病情好转归功于我自己, 我的抑郁症病情恶化也怪我自己。” (“I deserve the credit when my depression improves, and I am to blame when it worsens.”) in Version 1 and “我的抑郁症变好变坏都在我自己。” (“Whether my depression gets better or worse is entirely up to myself.”) in Version 2. After panel discussions among all research members, we changed the translation of this item to “我自己决定了我的抑郁症变好还是变坏。” (“It is up to myself whether my depression gets better or worse.”), which is more likely to meet the target Chinese readers’ expectations that are shaped by their linguistic and cultural norms in the Chinese contexts.

Item 15, “it’s a matter of fate” was translated into “那就是命运的问题了” (“it’s a matter of fate”) in Version 1 and “那就是我的命” (“that’s my fate”) in Version 2. After panel discussions, we changed these translations to “那就是命运的安排了” (“it’s up to fate”), which was believed to be more natural and idiomatic and therefore more acceptable in expression than “那就是命运的问题了” and “那就是我的命” according to the Chinese audience’s linguistic habits and cultural conceptions.

Item 18, “The type of help I receive from other people determines how soon my depression improves.”, was translated into “我从其他人那里得到什么样的帮助决定了我的抑郁症病情好转的快慢。” (“The type of help I receive from other people determines how soon my condition improves.”) in Version 1 and “别人给我的照顾多一些, 我的抑郁症就好得快一些; 别人给我的照顾少一些, 我的抑郁症就好得慢一些。” (“When others care more for me, my depression gets better sooner; when others care less for me, my depression gets better later.”) in Version 2. Based on panel discussions among all research members, we decided to revise the translation to “其他人给予我什么样的帮助决定了我的抑郁症好转的快慢。” (“The type of help other people give me determines how soon my depression improves.”), which was thought to be more semantically equivalent to the original English Item but was not unanimously agreed upon among all research members. Due to the undetermined cultural comprehensibility of this translation, we decided to leave it to cognitive debriefing during pilot testing with a small number of target Chinese readers for final decision and revision.

Based on the discussion of the problematic translations of the items above, we reached a consensus on the translated version of the preliminary initial Chinese MHLC From C, as shown in Table 3.4. This version was pilot tested among a certain number of native Chinese patient participants in the following step of adaptation.

Table 3.4 Preliminary initial Chinese MHLC Form C
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3.3.1.3 Pilot Testing of the Preliminary Initial Translated Chinese Version of the MHLC from C with a Chinese Sample: Cognitive Debriefing

During the pilot testing, the ten recruited native Chinese patient participants provided open feedback on whether and how they understood the translated and adapted scale. They raised some problems with the clarity and comprehensibility of the preliminary initial Chinese MHLC From C, although they believed that the whole translated scale was largely relevant to Chinese culture. In other words, there were not challenging questions and concepts irrelevant to Chinese culture (i.e., they were relevant to the participants’ daily life), but there were issues of linguistic accessibility (i.e., they were unexpected or ambiguous to the participants) (Shan & Ji, 2023). Specifically, “病情” in some translated items is redundant according to colloquial Chinese expression; “那是命运的安排了” in translated Item 15 and “恶化” in some translated items still needs to be made more colloquial, understandable, and acceptable to Chinese readers, especially to those with low educational attainments; Item 12, “影响我抑郁症病情的主要因素是我自己的所作所为。”, needs recasting in terms of the sequence of expression; Chinese expressions feature verbal phrases instead of nominal phrases, for example, “我自己行为” in translated Item 1 should be changed to “我自己怎么做”; some addition or deletions need to be made to make the translated items more culturally understandable and acceptable, for example, “我的抑郁症就顺其自然吧” in translated Item 2 should be changed to “我的抑郁症好转还是变坏就顺其自然吧”; etc. There were still more problems pointed out by the participants, which were rectified in Table 3.5.

Table 3.5 Final version of the Chinese MHLC Form C which is glossed in English
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Taking into consideration all comments and suggestions from the participants who took part in the cognitive debriefing, we not only improved the face validity (Shan & Ji, 2023) and the conceptual, semantic, and content equivalence (Sousa & Rojjanasrirat, 2011) but also further adjusted the structure of sentences used in the translated Chinese instrument, to make the final translated version easily understood by the target Chinese patient populations before psychometric testing (Sousa & Rojjanasrirat, 2011). As a result, all translated items were modified to varying degrees. The final version of the translated and adapted Chinese MHLC Form C is presented in Table 3.5.

As Brislin (1980) observes, critical issues negatively impact many translation studies, even when certified translators are used. Our discussion above supports Brislin’s (1980) observation. This is due primarily to three factors: (1) some translators’ inadequate awareness of the rigorous translation requirements for cross-cultural studies; (2) their literal translation and insufficient emphasis on cultural nuances; and (3) challenges posed by colloquial expressions, slang and jargon, idiomatic phrases, and emotionally evocative words (Sperber, 2004). Through the three steps of translation and adaptation above, we managed to generate the final version of the Chinese MHLC Form C, which we made maximally relevant, understandable, and acceptable to Chinese readers in the Chinese cultural contexts to the maximum of our potential. This version was then used to classify Chinese patients into different clusters and to identify associated factors.

3.3.2 Using the Chinese MHLC Form C to Classify Patients and Identifying Factors Associated with Low Self-efficacy

3.3.2.1 Descriptive Statistics

Table 3.6 presents the descriptive statistics of the data collected from the patient participants. All data in the 988 returned questionnaires were valid. The patients had a mean age of 42.85 (SD = 11.544) years. 45% (n = 443) of them were men. The mean score for education was 3.21 (SD = 1.474), showing that their average educational level was between Year 12 and diploma. The mean score for their self-reported disease knowledge was 2.42, indicating that they thought that their knowledge of disease was between ‘a lot’ and ‘some.’ The mean scores of the three functional items on the AAHLS scale were 2.06 (SD = 0.735), 2.13 (SD = 0.969), and 2.09 (SD = 0.741), respectively. These mean scores indicate that they ‘sometimes’ needed help to read and comprehend health information and complete official documents and were ‘sometimes’ able to identify and secure others’ help. The mean scores of the three communicative items on the AAHLS scale were 1.74 (SD = 0.754), 1.87 (SD = 0.745), and 1.88 (SD = 0.744), respectively. These mean scores indicate that when they talked to a doctor or nurse, they ‘often’ or ‘sometimes’ gave them all the information they needed, they ‘often’ or ‘sometimes’ asked the questions they needed to ask, and they ‘often’ or ‘sometimes’ made sure they explained anything that they did not understand. The mean scores of Items 1–5 on the critical health literacy sub-scale of the AAHLS scale were 1.97 (SD = 0.752), 1.94 (SD = 0.728), 1.91 (SD = 0.746), 2.01 (SD = 0.730), 1.97 (SD = 0.734), and 1.56 (SD = 0.496), respectively. These mean scores indicate that they ‘sometimes’ found out lots of different information about their health, they ‘sometimes’ thought carefully about whether health information made sense in their particular situation, they ‘sometimes’ tried to work out whether information about their health could be trusted, they ‘sometimes’ questioned their doctor or nurse’s advice based on their own research, they ‘sometimes’ thought that there were plenty of ways to have a say in what the government did about health, and they were inclined to believe that “good housing, education, decent jobs, and good local facilities” mattered most for their health. The scores for the 8 items on the eHEALS ranged from 2.83 (SD = 1.174) to 2.96 (SD = 1.179), indicating their uncertainty about their skills to use eHealth resources and interventions. The mean score for each item on the GHNT scale was 1.56 (SD = 0.497), 1.18 (SD = 0.383), 1.21 (SD = 0.406), 1.93 (SD = 0.333), 1.84 (SD = 0.370), and 1.77 (SD = 0.420), showing that a large proportion of participants answered the 6 questions on the GHNT scale incorrectly, especially questions 1 (551/988, 55.8%), 4 (908/988, 91.9%), 5 (826/988, 83.6%), and 6 (763/988, 77.2%). As with their scoring performance on the Multidimensional Health Locus of Control (MHLC) Scales (MHLC) Form C, they averagely scored 18.21 (SD = 4.790), 16.87 (SD = 4.803), 10.36 (SD = 3.5393), and 8.44 (SD = 2.915) on the ‘Internal,’ ‘Chance,’ ‘Doctor,’ and ‘Powerful Others’ subscales, respectively. The determined response of ‘slightly disagree’ for the ‘Internal’ subscale indicates that they somehow did not believe in their internal drives to maintain healthy. The determined response between ‘moderately disagree’ and ‘slightly disagree’ for the ‘Chance’ subscale implies that they were generally less likely to attribute their health to a matter of chance. The determined response between ‘slightly disagree’ and ‘slightly agree’ for the ‘Doctor’ subscale means that they were generally uncertain about the role of doctors in the maintenance of their own health. The determined response between ‘moderately disagree’ and ‘slightly disagree’ for the ‘Powerful Others’ subscale means that they generally did nor believe in the role of others in the maintenance of their own health.

Table 3.6 Descriptive statistics of the data collected (N = 988)
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3.3.2.2 Model Fit Statistics

Table 3.7 and Fig. 3.1 shows the model fit statistics of the latent class analysis. The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) provide measures of model performance. Smaller AIC and BIC are indicative of better model performance. Indexes like the Lo-Mendell-Rubin likelihood (LL) ratio test, and the bootstrap likelihood ratio test examined whether adding clusters would significantly improve model performance. We took into consideration all the factors and decided to opt for a 2-cluster solution for better model performance and simplicity to guide the subsequent qualitative analyses, as shown in Table 3.8.

Table 3.7 Model fit statistics for male data
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Fig. 3.1
figure 1

Model fit statistics changes. AIC: Akaike information criterion. BIC: Bayesian information criterion. LL: Lo-Mendell-Rubin likelihood

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Table 3.8 Posterior probabilities of response across latent clusters
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3.3.2.3 Profiling of 2 Latent Clusters

Cluster 1—Low Self-efficacy Group

Patient participants in Cluster 1 had low (9–18) to medium scores (19–27) on the ‘Internal’ sub-scale (with conditional probabilities higher than 0.5 until the internal sum score of 27), suggesting a mix of a less inclination and a slight inclination to believe in their own capability to manage self-health. For example, they were more likely to ‘strongly disagree’ (coding 1), ‘moderately disagree’ (coding 2), ‘slightly disagree’ (coding 3), or ‘slightly agree’ (coding 4) with statements such as ‘If my depression worsens, it is my own behavior which determines how soon I will feel better again’ (Item 1 on the Chinese depression-specific MHLC Form C), ‘I am directly responsible for my depression getting better or worse’ (Item 6 on the Chinese depression-specific MHLC Form C), and ‘Whatever goes wrong with my depression is my own fault’ (Item 8 on the Chinese depression-specific MHLC Form C).

Patients in Cluster 1 also had low (4–9) to medium scores (10–13) on the ‘Doctor’ sub-scale (with conditional probabilities higher than 0.5 until the internal sum score of 13), suggesting that they had limited trust in medical and health professionals and the health benefits of adhering to their recommendations and advice. For example, they were more likely to ‘strongly disagree’ (coding 1), ‘moderately disagree’ (coding 2), ‘slightly disagree’ (coding 3), or ‘slightly agree’ (coding 4) with statements such as ‘If I see my doctor regularly, I am less likely to have problems with my depression’ (Item 3 on the Chinese depression-specific MHLC Form C).

Patients in Cluster 1 had more spread scores across the ‘Other People’ sub-scale ranging from 4 to 18, suggesting that while some patients in Cluster 1 were unlikely to see the influence of others’ behaviors on their own health as significant, other patients in this cluster were likely to see the influence of others’ behaviors on their own health as significant. For example, patients in this cluster were likely to ‘strongly disagree’ (coding 1), ‘moderately disagree’ (coding 2), ‘slightly disagree’ (coding 3), ‘slightly agree’ (coding 4), ‘moderately agree’ (coding 5), or ‘strongly agree’ (coding 6) with statements such as ‘Other people play a big role in whether my condition improves, stays the same, or gets worse’ (Item 7 on the Chinese depression-specific MHLC Form C), ‘In order for my condition to improve, it is up to other people to see that the right things happen’ (Item 10 on the Chinese depression-specific MHLC Form C), and ‘The type of help I receive from other people determines how soon my condition improves’ (Item 18 on the Chinese depression-specific MHLC Form C).

Patients in Cluster 1 had low (11–18) to medium scores (19–28) on the ‘Chance’ sub-scale, suggesting that while some people in this cluster did not believe in the role of luck in one’s health management, others did ‘slightly’ agree with statements, such as ‘As to my condition, what will be will be’ (Item 2 on the Chinese depression-specific MHLC Form C), ‘Most things that affect my condition happen to me by chance’ (Item 4 on the Chinese depression-specific MHLC Form C), ‘Luck plays a big part in determining how my condition improves’ (Item 9 on the Chinese depression-specific MHLC Form C), ‘Whatever improvement occurs with my condition is largely a matter of good fortune’ (Item 11 on the Chinese depression-specific MHLC Form C), ‘If my condition worsens, it's a matter of fate’ (Item 15 on the Chinese depression-specific MHLC Form C), and ‘If I am lucky, my condition will get better’ (Item 16 on the Chinese depression-specific MHLC Form C).

Cluster 2—Moderate Self-efficacy Group

Patients in Cluster 2 showed two scenarios. Some had high scores on the ‘Internal’ sub-scale ranging from 28 to 34, suggesting that they had stronger beliefs in their own capability to manage their health. Their responses to the questions of the ‘Internal’ scale were more likely to be ‘slightly agree,’ ‘moderately agree,’ or ‘strongly agree’ with statements of the Chinese depression-specific MHLC Form C stressing the importance of self-discipline and self-management to achieve optimal health outcomes when it comes to the prevention and treatment of depression. For example, people in Cluster 2 were agreeable with statements like ‘the main thing which affects my condition is what I myself do’ (Item 12 on the Chinese depression-specific MHLC Form C), ‘I deserve the credit when my condition improves and the blame when it gets worse’ (Item 13 on the Chinese depression-specific MHLC Form C), and ‘If my condition takes a turn for the worse, it is because I have not been taking proper care of myself’(Item 17 on the Chinese depression-specific MHLC Form C). In contrast, other patients had low scores on the ‘Internal’ sub-scale ranging from 6 to 8, suggesting that they were more likely to ‘strongly disagree’ with statements of the Chinese depression-specific MHLC Form C stressing the importance of self-discipline and self-management to achieve optimal health outcomes when it comes to the prevention and treatment of depression.

Patients in Cluster 2 also displayed two scenarios. Some had higher scores on the ‘Doctor’ sub-scale, ranging from 14 to 18, suggesting that they had moderate to high levels of trust in health and medical professionals and the importance of adherence to their advice to achieve better health outcomes. Their responses to the questions of the ‘Doctor’ sub-scale were more likely to be ‘moderately agree’ or ‘strongly agree’ with statements of the Chinese depression-specific MHLC Form C highlighting the importance of seeking medical support to prevent, diagnose, and treat depression. For example, ‘whenever my condition worsens, I should consult a medically trained professional.’ (Item 5 on the Chinese depression-specific MHLC Form C), ‘Following doctor’s orders to the letter is the best way to keep my condition from getting any worse’ (Item 14 on the Chinese depression-specific MHLC Form C). By contrast, other patients had the lowest score of 3 on the ‘Doctor’ sub-scale, suggesting that they had the lowest level of trust in health and medical professionals and the importance of adherence to their advice to achieve better health outcomes. Their responses to the questions of the ‘Doctor’ sub-scale were more likely to be ‘strongly disagree’ with statements of the Chinese depression-specific MHLC Form C highlighting the importance of seeking medical support to prevent, diagnose, and treat depression.

Patients in Cluster 2 had a very high score (3) on the ‘Other People’ sub-scale, suggesting that all of them were more unlikely to associate their own depression outcomes with other people in their lives.

Chinese participants in Cluster 2 were divided on the ‘Chance’ sub-scale, with some people having very low scores (6–10) and others having very high scores (29–30). It indicates that a polarized view regarding the role of chance in their health and well-being existed among this group of patients, in a similar way that a polarized view was displayed on the role of internal motivations and doctors in terms of the prevention and treatment of depression.

Table 3.9 shows descriptive statistics of the two latent clusters representing the two levels of self-efficacy among the study participants. The low self-efficacy group (Cluster 1, n = 716) represented 72.5% (716/988) of the total sample. They had an average mean of 17.79 (SD = 1.44) on the ‘Internal’ scale, an average mean of 17.67 (SD = 0.15) on the ‘Chance’ scale, an average mean of 9.13 (SD = 0.10) on the ‘Doctor’ scale, and an average mean of 8.76 (SD = 0.10) on the ‘Other People’ scale. The moderate self-efficacy group (Cluster 2, n = 272) represented 27.5% (272/988) of the total sample. They had an average mean of 19.50 (SD = 4.23) on the internal scale, an average mean of 14.37 (SD = 0.39) on the ‘Chance’ scale, an average mean 14.23 (SD = 0.18) on the ‘Doctor’ scale, and an average mean 7.43 (SD = 0.24) on the ‘Other People’ scale

Table 3.9 Descriptive statistics of the latent clusters
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Next, we compared the differences between the two clusters across the four sub-scales. The result of the Welch Test in Table 3.10 shows that there were statistically significant differences among the two clusters representing two distinct levels of self-efficacy among the study participants in their scores on the ‘Internal,’ ‘Chance,’ ‘Doctor,’ and ‘Other People’ sub-scales.

Table 3.10 Robust tests of equality of means (welch test)
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3.3.2.4 Factors Associated with the Low Self-efficacy

Table 3.11 shows that the conditional probabilities of all variables within the 2 identified clusters of self-efficacy. From these conditional probabilities, Cluster 1, the low self-efficacy subgroup of patient participants were found to be closely associated with particular factors to be presented below.

Table 3.11 Conditional probabilities of all variables within each cluster
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Older Age

Table 3.11 shows that the conditional probabilities of age groups within the 2 identified clusters of self-efficacy. From this table, patients of low self-efficacy were more likely to be averagely aged 45.7 years old. In contrast, patients of moderate self-efficacy were more likely to be averagely aged 35.5 years old.

Male Sex

Table 3.11 shows that the conditional probabilities of genders within the 2 identified clusters of self-efficacy. As can be seen, 51.3% of the low-efficacy cluster were men, compared with 72.2% of the moderate-efficacy cluster being women.

Limited Educational Attainment

Table 3.11 shows that the conditional probabilities of different levels of educational attainment within the 2 identified clusters of self-efficacy. It can be seen that patients of low self-efficacy were more likely to have lower levels of education (Year 6 to Year 12). In contrast, patients of moderate self-efficacy were more likely to have adequate to high educational levels (diploma, university graduate, postgraduate or above).

Higher Level of Self-reported Disease Knowledge

Table 3.11 shows that the conditional probabilities of different levels of self-reported disease knowledge within the 2 identified clusters of self-efficacy. It is clear that just below 60% of patient participants of the low self-efficacy cluster were more likely to report knowing ‘very well’ or ‘a lot’ about diseases. In contrast, over 60% of patients of the moderate self-efficacy cluster were more likely to report knowing ‘some’ or ‘very limited’ about diseases.

Limited Functional Health Literacy

From Table 3.11, over 70% of patients of the low self-efficacy cluster were more likely to ‘often’ or ‘sometimes’ need help to read and comprehend health information and complete official documents, and over 60% of patients of this cluster were more like to be ‘often’ or ‘sometimes’ unable to identify and secure others’ help. In contrast, over 90% of patients of the high self-efficacy cluster were more likely to ‘sometimes’ or ‘rarely’ need help to read and comprehend health information and complete official documents, and were more likely to be ‘often’ or ‘sometimes’ able to identify and secure others’ help.

Limited Communicative Health Literacy

Table 3.11 shows that around about 70% of patients of low self-efficacy versus over 90% of patients of moderate self-efficacy were more likely to ‘often’ or ‘sometimes’ give a doctor or nurse all the information they needed, ‘often’ or ‘sometimes’ ask the questions they needed to ask, and ‘often’ or ‘sometimes’ make sure a doctor or nurse explained anything that they did not understand when they talked to a doctor or nurse.

Limited Critical Health Literacy

It can be seen from Table 3.11 that 62% of patients of the low-efficacy cluster were inclined to believe that good housing, education, decent jobs, and good local facilities mattered most for their health while 58% of patients of the moderate-efficacy cluster were more likely to consider that quality Health Information mattered most for their health condition.

Limited Digital Health Literacy

Table 3.11 shows that around 50% of patients of low self-efficacy were less likely to know where to find useful information on the internet, to know the means and methods to identify useful health information on the internet, and to agree that they had the skills and knowledge that enabled them to navigate electronic health platforms and find helpful health-related information. In contrast, approximately 40–50% of patients of adequate self-efficacy were more likely to agree or strongly agree that they were equipped with such essential skills and knowledge.

Limited Health Numeracy Literacy

Table 3.11 shows that 88.5% of patients of the low self-efficacy cluster answered question 6 on the GHNT scale incorrectly while 52.4% patients of the adequate self-efficacy cluster answered this question correctly.

3.4 Discussion

3.4.1 Principal Findings

3.4.1.1 Translation and Adaptation of the Chinese MHLC Form C

While it is extremely challenging to make a translated instrument culturally relevant, comprehensible, and acceptable to the target readers, we successfully translated and adapted the MHLC Form C into a depression-specific Chinese version which we believed to display a high degree of relevance, comprehensibility, and acceptability in the context of Chinese culture. A total of three steps adopted in the entire translation and adaptation process ensured the semantic equivalence and cultural appropriateness of the Chinese MHLC Form C, including (1) independently translating the original English MHLC Form C by two bilingual and bi-cultural translators whose native language is Chinese, (2) comparing not only the two independent translated versions but also these two version with the original English MHLC Form C to decide on the preliminary initial translated version, and (3) improving the preliminary initial translated version through cognitive debriefing through pilot testing it with a small numbers of participants.

Choosing qualified bilingual and bi-cultural translators whose mother tongue is the target language is the prerequisite for quality translation of an instrument. Before selecting competent translators in this study, we fully considered the fact that qualified translators are not always sufficiently knowledgeable in specialized subject areas related to some scales and are frequently unable to translate the content area of medical materials (Maneesriwongul & Dixon, 2004). One translator (Meng Ji) we used is a competent bilingual and bi-cultural translator who is a native Chinese speaker who has been living in Australia for many years and who has relatively rich experience in engaging in the translation and translation studies of health and medical materials, therefore largely warranting the quality of the original English MHLC Form C into Chinese. Another translator (Yi Shan) is also a competent bilingual and bi-cultural translator who is also a native Chinese speaker but who hasn’t lived in an English-speaking country for a long time and accumulated adequate experience in engaging in the translation and translation studies of health and medical materials. Yi Shan’s relatively less adapted translation of the original English MHLC Form C confirms the importance of sufficient knowledge about specialized subject areas related to the scale to be translated.

Regardless of the competence of the selected translators, especially Meng Ji, the Chinese MHLC Form C may be potentially insufficiently relevant, understandable, and acceptable in terms of the wordings and sentence structures of some items. Considering this possible insufficiency, we made a systematic comparison both between the two Chinese versions and between these two translated versions and the original English version, informed by Tang and Dixon (2002). Considering that the form can be purposefully changed to ensure equivalence of meaning (Sperber, 2004), we used some translation techniques including addition, deletion, substitution, omission, recasting, etc., therefore changing the form of the original text (Shan et al., 2023a, 2023b). We found these strategies effective in this study, contrary to the finding of Sperber (2004), who regarded these techniques as common translation errors. Through systematic comparisons and corresponding revisions, we effectively improved the cultural relevance, comprehensibility, and acceptability of the Chinese MHLC Form C.

In addition to the aforementioned methods of translation and adaptation, we used the approach of cognitive debriefing during testing the Chinese MHLC Form C with a small number of monolingual Chinese-speaking participants, which is imperative to validate the clarity and appropriateness (relevance) of the target-language version (Maneesriwongul & Dixon, 2004).

3.4.1.2 Efficacy Clusters and Associated Factors Identified

We identified 2 subgroups of patient participants, the low and moderate self-efficacy groups, which represented 72.5 and 27.5% of the total sample respectively. Patients in the low self-efficacy cluster (Cluster 1, 72.5%) had the following characteristics: (1) being less likely to believe in their own capability to achieve optimal outcomes in the prevention and treatment of depression; (2) having limited trust in medical and health professionals and the health benefits of adhering to their recommendations and advice; (3) having mixed views on the influence of others’ behaviors on their own health; and (4) having mixed views on the role of luck in one’s health management. Patients in the moderate self-efficacy cluster (Cluster 2, 27.5%) displayed distinct psychological traits. They had polarized views regarding the role of chance, internal motivations, and doctors in terms of the prevention and treatment of depression. All of them were more unlikely to associate their own depression outcomes with other people in their lives. In addition, we identified nine factors that were significantly associated with low self-efficacy, including (1) older age, (2) male sex, (3) limited educational attainment, (4) higher level of self-reported disease knowledge, (5) limited functional health literacy, (6) limited communicative health literacy, (7) limited critical health literacy, (8) limited digital health literacy, and (9) limited health numeracy literacy.

3.4.2 Implications

This study can provide some implications for clinical practice, health education, medical research, and public health policy-making. First, to translate scales for use in the target language and culture, rigorous translation and adaptation steps must be undertaken to ensure the cultural relevance, comprehensibility, and acceptability of the translated instruments. Translation is a challenging task, which calls for skill, knowledge, and experience (Sperber, 2004). Rigorous translation procedures, cultural nuances, jargon, idiomatic phrases, and emotionally evocative words (Sperber, 2004) all make the already challenging translation task even more complicated (Shan et al., 2023a, 2023b). To overcome these difficulties, we not merely carefully selected translators but also rigorously applied translation and adaptation strategies. As a result, we managed to successfully convey the original meanings and intents by choosing culturally equivalent linguistic expressions (Sperber, 2004), which were largely relevant, understandable, and acceptable to Chinese readers in the Chinese cultural contexts.

The two self-efficacy clusters and nine factors contributing to low self-efficacy can serve as important indicators for screening male patients with low self-efficacy to deliver more targeted education and more effective interventions to enhance their self-efficacy. Knowledge, skills, beliefs, and practices associated with the low self-efficacy class and the contributing factors could be integrated into public health education about and interventions in health beliefs about bladder cancer prevention and treatment among male patients to enhance their self-efficacy. Medical researchers can gain some insights into the topic of low self-efficacy and the contributing factors. Informed by this study, they could identify patients with low self-efficacy among their ethnic and socioeconomic groups, verify the contributing factors ascertained in this study, and find more contributors in future studies. Finally, our research results and findings can provide some implications for public health policy-making in the future.

3.4.3 Limitations

This study has some limitations. First, we did not test the internal consistency and test–retest reliability of the newly-developed Chinese MHLC Form C, although we used it to classify patient participants into two clusters. In future studies, we need to validate its reliability before applying it for other research purposes. Second, the generalizability of our research results and findings may be limited. The recruitment of patients from only one hospital was most likely to make the results and findings less generalizable to populations in other provinces in China and to patients in different linguistic and cultural communities worldwide. Further research is warranted to validate the results and findings among populations of diverse ethnic and sociocultural backgrounds. Third, the self-reported nature of the collected data may result in some bias. As claimed in Van der Varrt et al. (2011), self-reported literacy skills are not necessarily consistent with the actual abilities to comprehend, utilize, and appraise online health information. More objective measures need to be developed to increase the reliability and consistency of assessment of various health literacy and health beliefs and self confidence among culturally and linguistically diverse people. Finally, comparison could not sufficiently be made with previous studies due to the scarcity of relevant literature. Hopefully, our study can attract close attention from researchers, who can further examine this topic to add to the body of literature and expand knowledge, which could promote academic conversation around such a topic of social significance.

3.4.4 Conclusions

We used the depression-specific Chinese version to classify the patient participants into different latent classes according to their attitudes towards and beliefs about the prevention and treatment of depression, and identified significant factors that were closely associated with the low-efficacy cluster to provide essential implications for the delivery of tailored education and interventions and the administration of targeted prevention and treatment. After rigorous translation and adaptation procedures, we developed a culturally relevant, understandable, and acceptable Chinese MHLC Form C that is depression specific. Using this newly developed scale, we identified two subgroups defined as the low and moderate self-efficacy clusters which represented 72.5 and 27.5% of the total sample respectively. Patients in the low self-efficacy cluster (Cluster 1, 72.5%) had the following characteristics: (1) being less likely to believe in their own capability to achieve optimal outcomes in the prevention and treatment of depression; (2) having limited trust in medical and health professionals and the health benefits of adhering to their recommendations and advice; (3) having mixed views on the influence of others’ behaviors on their own health; and (4) having mixed views on the role of luck in one’s health management. Patients in the moderate self-efficacy cluster (Cluster 2, 27.5%) displayed distinct psychological traits. They had polarized views regarding the role of chance, internal motivations, and doctors in terms of the prevention and treatment of depression. All of them were more unlikely to associate their own depression outcomes with other people in their lives. In addition, we identified nine factors that were significantly associated with low self-efficacy, including (1) older age, (2) male sex, (3) limited educational attainment, (4) higher level of self-reported disease knowledge, (5) limited functional health literacy, (6) limited communicative health literacy, (7) limited critical health literacy, (8) limited digital health literacy, and (9) limited health numeracy literacy. This was the first study that investigated the attitudes towards and beliefs about the prevention and treatment of depression among patients in mainland China. Given the rising prevalence of the depressive disorder worldwide and in mainland China in recent years, the low self-efficacy cluster and associated contributing factors identified in this study can provide essential implications for clinical practice, health education, medical research, and health policymaking.