|Year : 2018 | Volume
| Issue : 2 | Page : 54-61
Theory of planned behavior, self-stigma, and perceived barriers explains the behavior of seeking mental health services for people at risk of affective disorders
Maryam Damghanian1, Mehran Alijanzadeh2
1 Nursing and Midwifery Care Research Center, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Health Services Management, School of Health, Qazvin University of Medical Sciences, Qazvin, Iran
|Date of Web Publication||29-Oct-2018|
Dr. Maryam Damghanian
School of Nursing and Midwifery, Tehran University of Medical Sciences, Nosrat St. Tohid Sq., Tehran
Source of Support: None, Conflict of Interest: None
Introduction: To use the theory of planned behavior (TPB) incorporated with self-stigma and perceived barriers to investigate the nature of help-seeking behaviors in a community sample at risk of anxiety or depression in Iran. Methods: Participants at risk of anxiety or depression screened by Hospital Anxiety and Depression Scale (n = 1011) completed the following questionnaires at baseline: Factors in TPB, Self-Stigma in Seeking Help Scale, and perceived barriers in seeking help. Two years later, their help-seeking behavior (i.e., visiting a specialist) was retrieved from their medical records. Models using TPB concepts and incorporated with self-stigma and perceived barriers were tested by structural equation modeling. Results: The effects of TPB concepts, self-stigma and perceived barriers on help-seeking behaviors (i.e., visiting a specialist for mental health problems) were supported by the excellent data-model fit indices: Comparative fit index = 0.997; Tucker–Lewis index = 0.965; root mean square of error approximation (RMSEA) = 0.028; and weighted RMSEA = 0.386. All the path coefficients were significant, except for the path between perceived barriers and help-seeking behavior. Perceived behavioral control had the strongest coefficient (standardized coefficient = 0.547); subjective norm had the weakest coefficient (standardized coefficient = 0.061). In addition, perceived barriers were indirectly associated with help-seeking behaviors. Conclusion: TPB is an effective model to explain the help-seeking behaviors for people at risk of anxiety or depression. In addition, self-stigma and perceived barriers may be simultaneously considered when clinicians want to prevent an individual with depression or anxiety from not seeking proper help on their mental health problems.
Keywords: Help-seeking, perceived barriers, self-stigma, theory of planned behavior
|How to cite this article:|
Damghanian M, Alijanzadeh M. Theory of planned behavior, self-stigma, and perceived barriers explains the behavior of seeking mental health services for people at risk of affective disorders. Soc Health Behav 2018;1:54-61
|How to cite this URL:|
Damghanian M, Alijanzadeh M. Theory of planned behavior, self-stigma, and perceived barriers explains the behavior of seeking mental health services for people at risk of affective disorders. Soc Health Behav [serial online] 2018 [cited 2019 Mar 26];1:54-61. Available from: http://www.shbonweb.com/text.asp?2018/1/2/54/244339
| Introduction|| |
People with mental illness often confront unfriendly treatments from the society or their community. The unfriendly treatments are primarily due to the misunderstandings toward the mental illness that result in public stigma, including negative attitude (i.e., stereotype), prejudice, and discrimination, to people suffering from mental illness.,, Under the environment filled with public stigma, people with mental illness or those with similar symptoms easily perceive or experience stigma, and are highly likely to endorse the public stigma into themselves as the self-stigma (also known as internalized stigma)., Self-stigma was found to be an obstacle for people with mental illness to recover: Yanos et al. found that self-stigma reduces one's sense of hope and self-esteem, and consequently results in social withdrawal, including using avoidant coping strategies. Similar statements have been proposed and found by Corrigan et al.,, that self-stigma substantially and negatively affect the self-esteem and self-efficacy of an individual with mental illness. Furthermore, self-stigma was found to be associated with many health-related outcomes and behaviors of individuals with mental illness, including their quality of life, depression, readiness to change, and adherence to treatment.,,,
The negative impacts of self-stigma are not limited to the above-mentioned issues; it may further affect individuals with mental illness or those with similar symptoms to seek help for their symptoms.,,, For example, self-stigma is one of the reasons that prevent these vulnerable individuals from seeking help. A national survey in Australia showed that stigmatizing attitudes were associated with intentions to seek help in young people if they had a problem similar to the mental disorder. In addition to the self-stigma, other perceived barriers such as time-consuming and expenditure are significantly associated with the help-seeking intentions and behaviors.,
Apart from the self-stigma and perceived barriers, the theory of planned behavior (TPB) proposed by Ajzen has been found to be a fundamental framework that well explains the help-seeking intention for people with mental illness.,,,, The TPB based on the principle of parsimony to postulate that three determinants (viz., attitude, subjective norm, and perceived behavioral control [PBC]) have impacts on the key component for an individual to perform a behavior, that is, behavioral intention. In terms of the three determinants, attitude that generated from behavioral beliefs indicates whether an individual favors or disfavors a behavior. The subjective norm that generated from normative beliefs portrays how an individual feels the social pressure on performing a behavior. PBC generated from control beliefs means to what extent for an individual to perceive the easiness or difficulty to engage in a behavior., With the significant identified elements, many studies found that TPB well explains many behaviors in various populations,,, including people with mental health problems.,,,
Studies on people with mental health problems found that attitude, subjective norm, and PBC in TPB could together explain 40%–60% of the help-seeking intention.,,, However, rarely have studies on people with mental health problems examined the help-seeking behaviors, that is, most studies ended up at behavioral intention in seeking help. Because the help-seeking behavior is a significant element and the ultimate outcome in the TPB, we should explore the association between the behavioral intention and the help-seeking behavior. Indeed, even we can enhance an individual's intention to seek help; the individual still cannot benefit from the enhanced intention if he or she does not engage in help-seeking behavior. Thus, investigating the relationship between behavioral intention and help-seeking behavior can provide additional information for health-care providers. Specifically, to what extent the enhanced behavioral intention can convert into the real behavior.
To fill with the gap of the current literature, this study aimed to use the TPB model to explain the help-seeking behaviors in a sample of the Iranian people at risk of anxiety or depression. In addition, we incorporated TPB model with both self-stigma and perceived barriers to investigate the nature of help-seeking behaviors in people at risk of anxiety or depression.
| Methods|| |
Participants and procedure
The study adopted a longitudinal design using two waves of data collection: One at baseline (attitude, subjective norms, PBC, self-stigma in seeking help, and perceived barriers in seeking help) and another at 2-year follow-up (help-seeking behavior). Data collection took place from March 2014 to August 2016, and two thousand Iranian adults were randomly approached from eight urban health centers through family records in Qazvin, Iran. Participants were eligible to include in the study if they (1) aged 18 years or older, (2) were willing to participate, and (3) reported mental health problems based on the cutoffs in the Hospital Anxiety and Depression Scale (score ≥7 for either anxiety or depression subscales).
Two trained nurses approached the potential participants by phone and asked them to visit urban health centers for an informational meeting. At the meeting, the nurses described the study purpose to the participants and asked them to complete baseline study measures (please refer to the instruments section below). Of the 2000 approached participants, 1763 (88.1%) adults agreed to participate, and they all completed the study measures accompanied by a written informed consent. More than half (n = 1011) of the participants fulfilled the third inclusion criterion, and their data were used for the following analyses. The present study was approved by the Ethics Committee of a University in Qazvin.
Attitude toward help-seeking
Attitude toward help-seeking was assessed using seven 5-point bipolar items (e.g., for me to seek mental health service is/would be: Extremely bad-extremely fine, extremely negative-extremely positive, extremely undesirable-extremely desirable, extremely unimportant-extremely important, extremely useless-extremely useful, extremely disagreeable-extremely agreeable, and extremely embarrassing-extremely unshameful), with higher scores indicating more positive help-seeking attitudes. Internal consistency of the seven items was satisfactory (α = 0.94).
Subjective norms toward help-seeking
Subjective norms were assessed using three items (e.g., my family views mental health service very negatively). All items were rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) with acceptable internal consistency (α = 0.79).
Perceived behavioral control
The PBC was assessed using three items (e.g., I am confident that I can seek mental health service if I wish to.). All items were rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) with satisfactory internal consistency (α = 0.84).
The help-seeking intention was assessed using three items (e.g., I intend to seek mental health service). All items were rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) with excellent internal consistency (α = 0.91).
Self-stigma in seeking help
Self-stigma was assessed using Self-Stigma of Seeking Help (SSOSH) Scale. The SSOSH consists of 10 items with each is rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree), and a higher score indicating a higher level of self-stigma. The SSOSH Persian version has been well translated with sound psychometric properties. Internal consistency of the SSOSH in this study was satisfactory (α = 0.89).
Perceived barriers in seeking help
The perceived barriers were assessed using six items (e.g., I think I can get the information about mental health service easily). All items were rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) with excellent internal consistency (α =0.88). In addition, higher scores indicate higher levels of perceived barriers.
The target behavior was the actual attendance of visiting a specialist (e.g., psychologist, psychiatrist, psychiatry nurse, or general practitioner) for mental health problems. Theoretically, help-seeking behavior was defined in the elements of Target (mental health specialists: Psychologist, psychiatrist, psychiatry nurse, and general practitioner), Action (visiting mental health specialists), Context (at a clinic), and Time (during the eligibility period). Based on the theoretically definition, we further operationally defined the help-seeking behaviors in the study as visiting a specialist. Specifically, we prospectively collected the help-seeking behaviors from the clinical records at the 2-year follow-up, and classified the behaviors into two categories: “No, did not visit in the follow-up” and “Yes, visited in the follow-up.”
Hospital anxiety and depression scale
The Hospital Anxiety and Depression Scale (HADS) was used to assess the depression or anxiety symptoms of a participant. There are 14 items and two domains (Depression and Anxiety) in the HADS: Each domain consists of 7 items with a 4-point Likert-type scale (scoring from 0 to 3). The cutoffs suggested for the HADS are ≤7 as normal; between 8 and 10 as mild; between 11 and 14 as moderate; ≥15 as severe depression/anxiety. Of the 1011 participants, 321 had no depression but had anxiety problems; 396 had no anxiety but had depression problems.
Participants' characteristics were analyzed using descriptive statistics, and the correlations between age, educational year, TPB elements, self-stigma in seeking help, and perceived barriers in seeking help were analyzed using Pearson correlation. Structural equation modeling (SEM) was applied to test the three models we proposed: Model 1 [Figure 1] only examined the TPB framework with the adjustment of demographic variables (age, gender, educational years, socioeconomic status, and employment). Model 2 additionally included self-stigma and perceived barriers in Model 1, and the two factors only linked to help-seeking behaviors (i.e., Model 2 added two more paths in Model 1). The same demographic variables were also controlled in Model 2. Model 3 [Figure 2] shared the same factors with Model 2, but it additionally included two more paths (self-stigma and perceived barriers to behavioral intention). That is, Model 3 additionally hypothesized that both self-stigma and perceived barriers were directly and indirectly associated with help-seeking behaviors.
|Figure 1: Mode 1 being the theory of planned behavior structural model (Age, gender, educational level, socioeconomic status, and employment were adjusted in the model). ***P<0.001|
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|Figure 2: Model 3 being the theory of planned behavior structural model combined with self-stigma and perceived barriers directly and indirectly associated with help-seeking behavior (Age, gender, educational level, socioeconomic status, and employment were adjusted in the model). *p<0.05; **p<0.01; ***p<0.001|
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To take care of the dichotomous nature of help-seeking behavior (yes vs. no) diagonally weighted least squares estimator was adopted in all SEM models. Before investigating each single association shown in the SEM paths, we first examine a series of fit indices to determine whether the model was supported: Comparative fit index (CFI) and Tucker–Lewis index (TLI) were set at 0.95 or above; root mean square of error approximation (RMSEA) set at 0.08 or below;,, weighted root mean square residual (WRMR) set at 0.10 or below. Sobel tests were further used to determine whether the mediated effects of behavioral intention were at the significance level.
Descriptive statistics and Pearson correlations were analyzed using SPSS 17.0 (IBM Corp. Armonk, New York: USA); all SEM models were conducted using lavaan package in the R software.
| Results|| |
[Table 1] demonstrates the demographic information of the participants: Slightly more than half of them were male (n = 558, 55.2%); mean (standard deviation [SD]) age was 27.59 (8.22) years; mean educational year was 6.45 (3.57); nearly two-thirds of them had a family size ≤5 (n = 628, 62.1%). Although 63.1% (n = 638) of the participants were not employed, only few (n = 17, 1.7%) were in poor socioeconomic status. In addition, [Table 2] shows the correlation matrix among the age, educational year, TPB elements, self-stigma, and perceived barriers.
|Table 2: Pearson correlations among age, educational year, theory of planned behavior factors, self-stigma, and perceived barriers|
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Model 1 had excellent data-model fit (CFI = 0.995, TLI = 0.955, RMSEA = 0.047, WRMR = 0.568), except for the significant Chi-square test (P = 0.040). Because fit indices support Model 1, we further examined the significance of each path coefficient. All the paths proposed using TPB were significant (all P < 0.001), and the PBC had the strongest association with behavioral intention (standardized coefficient = 0.656); and with help-seeking behaviors (standardized coefficient = 0.516). The relationship between subjective norm and behavioral intention was the weakest (standardized coefficient = 0.074). Attitude, subjective norm, and PBC together explained 61.9% of the behavioral intention; behavioral intention and PBC together explained 60.8% of the help-seeking behaviors [Figure 1]. In addition, Sobel tests showed that attitude (coefficient = 0.096, standard error [SE] =0.026, P < 0.001), subjective norm (coefficient = 0.043, SE = 0.014, P = 0.002), and PBC (coefficient = 0.281, SE = 0.052, P < 0.001) indirectly associated with help-seeking behaviors through behavioral intention [Table 3].
Model 2 showed worse fit indices (CFI = 0.945, TLI = 0.711, RMSEA = 0.081, WRMR = 1.114, χ2 = 29.786, P < 0.001) than did Model 1. In addition, most fit indices of Model 2 were not satisfactory, and we considered Model 2 was not supported. However, after correlating two additional paths (from self-stigma and perceived barriers to behavioral intention), Model 3 had all fit indices substantially improved (nonsignificant Chi-square test [P = 0.167], CFI = 0.997, TLI = 0.965, RMSEA = 0.028, and WRMR = 0.386). All the significant paths shown in Model 1 remained significant in Model 3 [Figure 2] with the similar trend: PBC had the strongest coefficient (standardized coefficient = 0.547) and subjective norm had the weakest coefficient (standardized coefficient = 0.061). Mediated effects of behavioral intention in the associations of TBP factors were also significant [Table 3]. Model 3 additionally portrayed that self-stigma (standardized coefficient = −0.112, P < 0.001) and perceived barriers (standardized coefficient = −0.099, P < 0.001) were negatively correlated with behavioral intention [Figure 2], and were indirectly associated with help-seeking behaviors through intention [Table 3]. Furthermore, the majority of the variances in behavioral intention (63.4%) and that in help-seeking behaviors (62.4%) were explained in Model 3.
In all models, age was significantly correlated with help-seeking behaviors (coefficient = 0.021, SE = 0.007, P = 0.001 for Model 1; coefficient = 0.017, SE = 0.007, P = 0.013 for Models 2 and 3) but not with behavioral intention (coefficient = 0.002, SE = 0.002, P = 0.310 for Model 1; coefficient = 0.001, SE = 0.002, P = 0.679 for Models 2 and 3); gender was neither significantly correlated with behaviors (P = 0.127 for Model 1 and 0.135 for Models 2 and 3) nor with intention (P = 0.174 for Model 1 and 0.187 for Models 2 and 3).
| Discussion|| |
Generally speaking, our findings agree with those of studies on similar populations (people with depression or people with mental illness): The TPB well explains the behavioral intention.,, We additionally extended the evidence from behavioral intention to help-seeking behaviors. That is, behavioral intention and PBC together explained ~ 60% of the variance in help-seeking behaviors. Thus, our results linked the TPB model to clinical practice. When healthcare providers want to enhance the help-seeking behavior of individuals with anxiety or depression, increasing their willingness in help-seeking is crucial. Furthermore, we demonstrated that attitude, subjective norm, and PBC were significant determinants to help-seeking intention. In addition to the TPB elements, self-stigma, and perceived barriers were possible obstacles associated with help-seeking behaviors. The aforementioned results were also consistent with what Mo and Mak and Yap et al. have found. Furthermore, self-stigma was directly and indirectly (through behavioral intention) associated with help-seeking behaviors; perceived barriers were only indirectly associated with help-seeking behaviors through behavioral intention.
Although our results generally in line with the studies adopting TPB,,, slightly differences were found. Specifically, Mak and Davis and we found that PBC had the strongest association with behavioral intention as compared with attitude and PBC. Both Mo and Mak and Schomerus et al. reported that the association between PBC and behavioral intention was the weakest. However, Schomerus et al. claimed that the low correlation between PBC and behavioral intention in their study may be due to the low internal consistency in their PBC measure (α =0.54). They proposed another reason: Health system with less restricted access to mental health services (e.g., the health system in German) may decrease the association between PBC and behavioral intention.
As for the weakest association between PBC and behavioral intention found in Mo and Mak, it could be explained by subjective norm with salient effects in their TPB model. Because subjective norm is dominant in their model, it may take over part of the associations between PBC and behavioral intention. Nevertheless, we agree with what Mak and Davis have suggested: Policies could target on external factors related to PBC (e.g., popularization, promotion and knowledge of mental health services, and affordable fee) because of the strong relationship between PBC and behavioral intention.
Similar to most studies,,,, we found that subjective norm had the lowest relationship with behavioral intention. The associations between attitude, PBC, and behavioral intention were relatively high, which suggest that the participants generally felt positively about their help-seeking intention. With such high confidence in their help-seeking intention, the association between subjective norm and behavioral intention is possibly to be diminished.,
In terms of the self-stigma and perceived barriers, we found that self-stigma played a more important role than did the perceived barriers. Many studies have discussed and demonstrated the impacts of self-stigma on willingness to change.,, A possible reason for the influence of willingness to change is the reduced hope and self-esteem; both are also contributed by self-stigma. Hence, health-care providers may want to design self-stigma reduction program to handle this issue. The association between perceived barriers and behavioral intention was modest in our findings, and Mo and Mak reported similar results that barriers only explained <1% of the behavioral intention. We additionally demonstrated that barriers seemed to have no relationship with help-seeking behaviors.
There are some limitations in the study. First, we did not have any psychiatrist to evaluate and diagnose the participants in anxiety or depression; therefore, we cannot ensure whether our proposed model is applicable for those who have a diagnosis given by psychiatrists. Future studies on people with the diagnosis are highly recommended to corroborate our findings. Second, we did not measure and control the prior help-seeking behavior; therefore, we may not completely ensure that the final help-seeking behavior was due to the TPB factors, or because of the prior behavior. Third, we adopted self-reports for self-stigma and perceived barriers, which are likely to be biased because of the social desirability. However, we justified that self-reports are the best methods to collect such information, and the bias may not be serious. Finally, although we used a longitudinal design to assess the associations between our proposed model and the help-seeking behavior, we still cannot ensure any causal effects. Future research using a true experimental study design to detect the causal effects is thus warranted.
| Conclusion|| |
Our results suggest that TPB is an effective model to explain the help-seeking behaviors for people at risk of depression or anxiety. In addition, self-stigma and perceived barriers are significant factors which may prevent an individual with depression or anxiety from seeking proper help on the mental health problem. Using our results, healthcare providers may want to design some interventions on enhancing the behavioral intention, reducing self-stigma, and minimizing the barriers for people with depression or anxiety. Thus, their help-seeking behaviors may be increased, and their health and quality of life may be improved subsequently.
The present paper is the outcome of a research project approved at Qazvin University of Medical Sciences. Hereby, the authors would like to appreciate Research vice chancellor of Qazvin University of Medical Sciences and Health Deputy of the university, authorities of the medical centers as well as all the participants for their participation and cooperation in this project.
Financial support and sponsorship
The project was financially supported by Research vice chancellor of Qazvin University of Medical Sciences.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Angermeyer MC, Dietrich S. Public beliefs about and attitudes towards people with mental illness: A review of population studies. Acta Psychiatr Scand 2006;113:163-79.
Chang CC, Lin CY, Gronholm PC, Wu TH. Cross-validation of two commonly used self-stigma measures, Taiwan versions of the internalized stigma mental illness scale and self-stigma scale-short, for people with mental illness. Assessment 2018;25:777-92.
Chang CC, Wu TH, Chen CY, Lin CY. Comparing self-stigma between people with different mental disorders in Taiwan. J Nerv Ment Dis 2016;204:547-53.
Pescosolido BA, Martin JK. The stigma complex. Annu Rev Sociol 2015;41:87-116.
Lin CY, Chang CC, Wu TH, Wang JD. Dynamic changes of self-stigma, quality of life, somatic complaints, and depression among people with schizophrenia: A pilot study applying kernel smoothers. Stigma Health 2016;1:29-43.
Picco L, Pang S, Lau YW, Jeyagurunathan A, Satghare P, Abdin E, et al.
Internalized stigma among psychiatric outpatients: Associations with quality of life, functioning, hope and self-esteem. Psychiatry Res 2016;246:500-6.
Yanos PT, Roe D, Markus K, Lysaker PH. Pathways between internalized stigma and outcomes related to recovery in schizophrenia spectrum disorders. Psychiatr Serv 2008;59:1437-42.
Corrigan PW, Rafacz J, Rüsch N. Examining a progressive model of self-stigma and its impact on people with serious mental illness. Psychiatry Res 2011;189:339-43.
Corrigan PW, Watson AC, Barr L. The self-stigma of mental illness: Implications for self-esteem and self-efficacy. J Soc Clin Psychol 2006;25:875-84.
Fung KM, Tsang HW, Corrigan PW, Lam CS, Cheung WM. Measuring self-stigma of mental illness in China and its implications for recovery. Int J Soc Psychiatry 2007;53:408-18.
Fung KM, Tsang HW, Corrigan PW. Self-stigma of people with schizophrenia as predictor of their adherence to psychosocial treatment. Psychiatr Rehabil J 2008;32:95-104.
Fung KM, Tsang HW, Cheung WM. Randomized controlled trial of the self-stigma reduction program among individuals with schizophrenia. Psychiatry Res 2011;189:208-14.
Mak HW, Davis JM. The application of the theory of planned behavior to help-seeking intention in a Chinese society. Soc Psychiatry Psychiatr Epidemiol 2014;49:1501-15.
Mo PK, Mak WW. Help-seeking for mental health problems among Chinese: The application and extension of the theory of planned behavior. Soc Psychiatry Psychiatr Epidemiol 2009;44:675-84.
Schomerus G, Matschinger H, Angermeyer MC. Attitudes that determine willingness to seek psychiatric help for depression: A representative population survey applying the theory of planned behaviour. Psychol Med 2009;39:1855-65.
Yap MB, Wright A, Jorm AF. The influence of stigma on young people's help-seeking intentions and beliefs about the helpfulness of various sources of help. Soc Psychiatry Psychiatr Epidemiol 2011;46:1257-65.
Kung WV. Cultural and practical barriers to seeking mental health treatment for Chinese Americans. J Community Psychol 2004;32:27-43.
Nsereko JR, Kizza D, Kigozi F, Ssebunnya J, Ndyanabangi S, Flisher AJ, et al.
Stakeholder's perceptions of help-seeking behaviour among people with mental health problems in Uganda. Int J Ment Health Syst 2011;5:5.
Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process 1991;50:179-211.
Ajzen I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol 2002;32:665-83.
Armitage CJ, Conner M. Efficacy of the theory of planned behaviour: A meta-analytic review. Br J Soc Psychol 2001;40:471-99.
Lin CY, Updegraff JA, Pakpour AH. The relationship between the theory of planned behavior and medication adherence in patients with epilepsy. Epilepsy Behav 2016;61:231-6.
Pakpour AH, Zeidi IM, Chatzisarantis N, Molsted S, Harrison AP, Plotnikoff RC. Effects of action planning and coping planning within the theory of planned behaviour: A physical activity study of patients undergoing haemodialysis. Psychol Sport Exerc 2011;12:609-14.
Pakpour AH, Zeidi IM, Emamjomeh MM, Asefzadeh S, Pearson H. Household waste behaviours among a community sample in Iran: An application of the theory of planned behaviour. Waste Manag 2014;34:980-6.
Vogel DL, Armstrong PI, Tsai PC, Wade NG, Hammer JH, Efstathiou G, et al.
Cross-cultural validity of the self-stigma of seeking help (SSOSH) scale: Examination across six nations. J Couns Psychol 2013;60:303-10.
Soheilian SS, Inman AG. Middle Eastern Americans: The effects of stigma on attitudes toward counseling. J Muslim Ment Health 2009;4:139-58.
Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361-70.
Julian LJ. Measures of anxiety: State-trait anxiety inventory (STAI), beck anxiety inventory (BAI), and hospital anxiety and depression scale-anxiety (HADS-A). Arthritis Care Res (Hoboken) 2011;63 Suppl 11:S467-72.
Cheng CP, Luh WM, Yang AL, Su CT, Lin CY. Agreement of children and parents scores on Chinese version of pediatric quality of life inventory 4.0: Further psychometric development. Appl Res Qual Life 2016;11:891-906.
Tsai MC, Strong C, Lin CY. Effects of pubertal timing on deviant behaviors in Taiwan: A longitudinal analysis of 7th
- to 12th
-grade adolescents. J Adolesc 2015;42:87-97.
Wu TH, Chang CC, Chen CY, Wang JD, Lin CY. Further psychometric evaluation of the self-stigma scale-short: Measurement invariance across mental illness and gender. PLoS One 2015;10:e0117592.
Cook KF, Kallen MA, Amtmann D. Having a fit: Impact of number of items and distribution of data on traditional criteria for assessing IRT's unidimensionality assumption. Qual Life Res 2009;18:447-60.
Sobel ME. Asymptotic confidence intervals for indirect effects in structural equation models. In: Leinhardt S, editor. Sociological Methodology. Washington, DC: American Sociological Association; 1982. p. 290-312.
Hagger MS, Chatzisarantis NL, Biddle SJ. A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: Predictive validity and the contribution of additional variables. J Sport Exerc Psychol 2002;24:3-32.
Hunter MS, Grunfeld EA, Ramirez AJ. Help-seeking intentions for breast-cancer symptoms: A comparison of the self-regulation model and the theory of planned behaviour. Br J Health Psychol 2003;8:319-33.
Chapman SC, Horne R, Chater A, Hukins D, Smithson WH. Patients' perspectives on antiepileptic medication: Relationships between beliefs about medicines and adherence among patients with epilepsy in UK primary care. Epilepsy Behav 2014;31:312-20.
Stefan H. Improving the effectiveness of drugs in epilepsy through concordance. Adv Clin Neurosci Rehabil 2009;8:15-8.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]