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Curr Psychol DOI 10.1007/s12144-016-9542-z

Receiving Online Psychological Counseling and its Causes: A Structural Equation Model Ahmet Erdem 1 & Salih Bardakci 1 & Şefika Erdem 1

# Springer Science+Business Media New York 2016

Abstract In this study, it is aimed at measuring the university students’ behaviors of receiving online counseling services and determining the causes which have a causal relationship with these behaviors. University students’ behaviors of receiving online counseling services and the causes of those behaviors are investigated through structural equation model based on Theory of Planned Behavior. In this study, four different data collection tools were developed to measure subjective norm about the online counseling, perceived behavioral control, intention and behavior. The attitude towards online counseling was measured using Online Counseling Attitude Scale, which was developed by Rochlen et al. (Measurement and Evaluation in Counseling and Development 37(2):95, 2004) and adapted into Turkish by Demirci et al. (International Journal of Psychology and Educational Studies 1(1):15–22, 2014). Internet anxiety was measured using Internet Anxiety Scale, which was developed by Joiner et al. (Computers in Human Behavior 23(3):1408– 1420, 2007) and adapted into Turkish by Akın (2012). The data of this study were collected from participants in two steps. In the first step which is the development of the scale, the data were collected from 150 students studying at faculty of education of a university in Central Black Sea Region during 2014–2015 academic year. In the second step which is the testing of the proposed model, the data were collected from a total of 480 students [319 (66.46%) female, 161 (33.54%) male] studying at faculty of education of the same university, but they are different from the participants in the first step. According the results, the proposed model estimated the * Ahmet Erdem [email protected]

1

Faculty of Education, Gaziosmanpaşa University, Tokat, Turkey

variance on the intention and behavior of receiving online counseling. The variance on the intention of receiving online counseling was affected by the internet anxiety most. In contrast with the argument of TPB, perceived behavioral control has no impact on intention, but has a direct and significant impact on behavior. Keywords Planned behavior theory . Online counseling . E-therapy

Introduction Psychological counseling services provided through internet are called in a variety of names such as online counseling/ therapy, e-counseling/therapy, web-based counseling/therapy, email counseling/therapy, cyber counseling and internet-based counseling (Pollock, 2006; McCrickard & Buttler, 2005; Elleven & Allen, 2004; Cook & Doyle, 2002; ManhalBaugus, 2001). This concept was defined in the early 2000s by USA National Board for Certified Counselors (NBCC) as the process of professional counselling and information transfer performed through internet in the event of a physical distance between the client and the counselor (as cited in ManhalBaugus, 2001). Today, counseling services about issues such as depression, family relations, substance abuse, anxiety, sexual problems, eating disorders, coping with grief, phobias, career counseling, and psychological dimensions of medical problems (Laszlo et al., 1999) are provided through websites founded by psychiatrists, psychologists, psychological counselors, marital/family therapists, and social workers (Yuen et al., 2012; Nguyen et al., 2004). E-mails, a variety of synchronous and asynchronous social interaction media, video conferences, e-bulletins, self-help guides, and assessment tests

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are used within these services (Kilroe, 2010a, b; Shaw & Shaw, 2006; Cook & Doyle, 2002; Childress, 2000; Barak, 1999). Starting from the mid-1990s in private practices, paid psychological counseling services and the demand increased significantly towards the end of 1999. During this period, there were more than 250 online psychological counseling websites and more than 400 specialists as well as 5.000–25.000 daily messages (Ainsworth, 2001; Freeny, 2001; Manhal-Baugus, 2001). The exact number of online therapists around the world or in Turkey is unknown; however, the Google© search for Bonline psychological counseling^ term yielded 550.000 result on April 10, 2016. Moreover, although there is no statistical data about the number of experts providing online counseling in Turkey, the search engine yielded 27.500 results for Turkey. This shows that there can be a considerable amount of demand for online counseling in Turkey. When the results are examined in general, it can be seen that counseling centers in large cities are providing online counseling to their customers. Online counseling is stated to have positive and negative sides (Finn & Holden, 2000; Hohenshil, 2000; Maheu & Gordon, 2000; Laszlo et al., 1999; Miller & Gergen, 1998; Graham, 1996; Shapiro & Shulman, 1996). According to Finn (2002), the limitations of online counseling are inability to catch the visual and verbal clues of the client; problems about communication, privacy and security; inability to intervene in emergencies; difficulty in settlement of the client’s and counselor’s roles, determination of the client’s strengths, continuity of the service, handling transference, determination of ethical and legal standards, and monitoring services; the lack of models with empirical validity; and costs. Some ethical dilemmas and risks are emphasized in literature especially about the privacy of the process (Banach & Bernat, 2000; Baur, 2000; Robson & Robson, 2000; Seuler, 2000; Waldron et al., 2000; Lebow, 1998; Lee, 1998; Pergament, 1998; Holmes, 1997). With the increase in the interest and demand for online psychological counseling, some professional bodies and International Society for Mental Health (ISMHO) developed various ethical principles in 1997 (ISMHO, 2000; ACA, 2005; APA, 2003; APA, 2002; NBCC, 2009; APA, 1997). American Psychological Association declared that the principles of service and ethics in face-to-face counseling are valid for other practices as well (APA, 1997). On the other hand, National Board for Certified Counselors (NBCC) emphasized the problems sourcing from the assessment of visual clues, explanation of coping methods to the clients, and the permission of parents for underagechildren (NBCC, 2009). In the first comprehensive study focusing on the ethical standards of online counseling in Turkey conducted by Turkish Psychological Association, these types of services were categorized into internet, video conference and chat applications under the title of BNon-

traditional Psychotherapy Environments^, and the ethical principles in face-to-face services are stated to be valid for the services in these types of environments (Turkish Psychological Association, 2004). The possible advantages of online counseling services were summarized by Finn (2002) as an alternative and beneficial way for those who can’t receive counseling service because of a variety of reasons such as the difficulty in transportation or geographical difficulties; physical, social or psychological isolation or disability; the costs; cultural difficulties; or being labelled for receiving counseling services. It is more comfortable for clients and it provides a steady support for the client to keep up with the society, which is a constantly changing big group (Reynolds & Morris, 2002). According to Titov et al. (2010), the number of clients preferring individual or group online counseling increased as the internet and smart phones became widespread. In their study, Bergstrom et al. (2010) determined that online counseling practices are as effective as face-to-face counseling sessions. In a study with high school students conducted by Lunt (2004), the participants stated that the possibility of getting in contact with their counselors when they need might make them feel good. In an empirical study carried out by Young (2005), participants stated that they wanted to receive online counseling because of anonymity and its ease. In a qualitative study, some of the participants stated that they received support from their counselors through online media while others stated that these services weren’t useful (Haberstroh et al. 2007). Within this context, online counseling services can be characterized as an important opportunity to increase the prevalence and effectiveness of counseling services with the help of countless advantages. Therefore, receiving online psychological counseling and the reasons behind this behavior are an important research problem. Today, the number of online counseling services in Turkey is high; however, it is a fact that this high number doesn’t increase the tendency to benefit from these services. As prerequisite for the behavior of benefiting from these services, attitudes towards online counseling can be determined and improved. At this point, another important variable can be adverse beliefs such as technology anxiety since it is likely for the participants’ approaches towards online counseling services to be affected by these beliefs. From this perspective in this study, it is aimed at measuring the university students’ behaviors of receiving online counseling services and determining the causes which have a causal relationship with these behaviors. In this study, university students’ behaviors of receiving online counseling services and the reasons behind those behaviors are investigated through a structural equation model based on Theory of Planned Behavior (Ajzen, 2006, 1991, 1985).

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Theory of Planned Behavior (TPB) is a behavior theory designed to explain or predict the behaviors which are demonstrated or likely to be demonstrated by people in specific situations (Fishbein & Ajzen 1975). This theory is based on the social psychology, and it is widely used to explain behaviors in a variety of disciplines (Bamberg, 1996; Piles & Schmidt, 1996; Cohen & Hanno, 1993). TPB argues that the primary predictor of a behavior is the intention. Intentions, on the other hand, are predicted by attitudes, perceived social pressure (subjective norms), and perceived behavioral control. According to this approach, there are three factors that affect the intention: attitude toward the behavior, perception of society (perceived social pressure), and behavior control, also known as perceived self-efficacy. In this model, intention is the mediating variable betweenbehavior and attitudes, subjective norms, and perceived behavioral control. Perceived behavioral control may affect the behavior directly and through intention (Ajzen, 2006; Fishbein & Ajzen, 1975). TPB can be viewed in Fig. 1. In this study, the behavior of receiving online counseling is investigated in terms of attitudes towards this behavior, subjective norm, perceived behavioral control, intention and internet anxiety.

Related Concepts and Hypotheses Attitude towards Behavior Kağıtçıbaşı (1999) defines the attitude as Ba tendency which is attributed to an individual and regularly forms the individual’s thoughts, emotions and behaviors about a psychological object.^ Attitude towards behavior, on the other hand, is the positive or negative view of the individual about the behavior, which is about to be demonstrated (Küçük 2011; Erten 2002). According to TPB, attitude toward a behavior is determined by accessible beliefs about the consequences of the behavior. These are called as behavioral beliefs. Each behavioral belief links the behavior to a certain outcome, or to some Fig. 1 Planned behavior model (Ajzen, 2006: 118)

other attribute such as the cost incurred by performing the behavior (Azjen, 2005). The attitude toward the behavior is determined by the person’s evaluation of outcomes associated with the behavior and by the strength of these associations. In TPB, attitude towards behavior can be explained by beliefs about the outcomes which the individual can reach when the related behavior is demonstrated and the values given to these outcomes by the individual (Ajzen, 1991, 2005; Ajzenet al. 1982; Fishbein & Ajzen, 1975). In other words, the outcome nurtures the behavior. Within this context, the hypotheses below can be developed: Subjective Norm (Perceived Social Pressure) Subjective norm defines the social pressure perceived by the individual about demonstrating the behavior (Fishbein & Ajzein, 1975). It is also expressed as the expectationsabout displaying or not displaying a behavior, held by individuals, institutions or foundations, who are important for the individual (Erten, 2002). Subjective norms the second major determinant of intentions in the TPB, are also assumed to be function of beliefs, but beliefs of a different kind, namely the person’s beliefs that specific individuals or groups approve or disapprove of performing the behavior; or that these social referents themselves engage or do not engage in it (Ajzen, 2005). If the individual believes that the reference groups, who seem important for the individual, will approve the behavior, he/she feels pressure to demonstrate that behavior. Similarly, if the individual believes that those reference groups will disapprove the behavior, he/she avoids that behavior (Kocagöz, 2010; Ajzen, 1991, 1985; Fishbein & Ajzen, 1975). The important thing here is the importance level attributed by the individual to these reference groups. Perceived Behavioral Control Perceived behavioral control can be defined as the individual’s beliefs about how hard or easy to demonstrate the related behavior (Erten, 2002). This situation is related to practicability and control beliefs, and it may facilitate or repress the

Attitude towards the Behavior

Subjective Norm

Perceived Behavioral Control

Subjective Norm (Perceived Social Pressure)

Intention

Behavior

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behavior depending on the frequency of factors such as internal control (knowledge, personal incompetency, ability, emotion) and external control (opportunities, dependence on others, barriers) (Kocagöz, 2010; Leroy et al., 2009; Connor, 1993). The final major predictor in the TPB, perceived behavioral control, is also assumed to be function of beliefs, this time beliefs about the presence of absence of factors that facilitate or impede performance of the behavior (Ajzen, 2005). According to TPB, perceived behavioral control has two effects on behavior; direct effect and indirect effect through intention. The direct effect of perceived behavioral control on behavior is explained by Ajzen (1991, 1985) as Bholding intention constant, the effort expended to bring a course of behavior to a successful conclusion is likely to increase with perceived behavioral control.^ Ajzen (1991) states that perceived behavioral control is most compatible with Bandura’s concept of perceived self-efficacy. In addition to this, he emphasizes theoretical differences between two concepts, and expresses that perceived behavioral control involves both self-efficacy and a belief that the display of a behavior is under the individual’s own control (Kaiser, 2006; Armitage & Conner, 1999; Manstead & Van Eekelen 1998; Terry & O’Leary, 1995; Bandura, 1992).

Within the framework of the literature and the model, the hypotheses of this study are presented below:

Internet Anxiety

The proposed model related to the hypotheses in this study can be seen in Fig. 2.

The concept of anxiety broadly involves beliefs that the duty won’t be fulfilled or will be difficult/dangerous to fulfill and negative reactions sourcing from these beliefs (Fiske et al. 1996; Cattell and Scheier 1961). The pioneer studies reveal that anxiety can lead to lack of self-esteem, avoidance behaviors, worry, fear, and tension (Nelson, 2015; Beauchemin et al., 2008). From this viewpoint, anxiety towards information technologies is the psychological characteristics which are sourced from adverse beliefs about the use of these technologies and creates a tendency to avoid the use of them (Cazan et al., 2016; Çevik & Baloğlu, 2007; Beckers & Schmidt, 2001; Anderson, 1996). At this point, internet anxiety can be considered to have a potential negative influence on individuals’ tendency to receive online counseling. Intention According to TPB, attitude towards the behavior, subjective norm and perceived behavioral control form the intention (Leroy et al. 2009; Ajzen 1991, 1988). Ajzen (1991) defines the intention as the individual’s level of eagerness to display a behavior and the intensity of the effort planned to be made. Most researchers in the field of social psychology accept that an intention is required for a behavior to be demonstrated, and within this context, intention plays a mediating role between the behavior and other variables (Ajzen 2008; Davis et al. 1992; Fishbein and Ajzen 1975).

H1: Positive attitudes towards receiving online counseling have a positive and significant impact on the intention of receiving online counseling. H2: Negative attitudes towards receiving online counseling have a negative and significant impact on the intention of receiving online counseling. H3: Subjective norms about receiving online counseling have a positive and significant impact on the intention of receiving online counseling. H4: Perceived behavioral control about receiving online counseling has a positive and significant impact on the intention of receiving online counseling. H5: Perceived behavioral control about receiving online counseling has a positive and significant impact on the behavior of receiving online counseling. H6: Internet anxiety has a negative and significant impact on the behavior of receiving online counseling. H7: The intention of receiving online counseling has a positive and significant impact on the behavior of receiving online counseling.

Method In this section, firstly the findings about model adaptation are presented. Then, the results of the path analysis, which explains the actual results of the study, are explained in the light of the hypotheses. Participants The data of this study were collected from participants in two steps. In the first step which is the development of the scale, the data were collected from 150 students studying at faculty of education of a university in Central Black Sea Region during 2014–2015 academic year. This number is enough for the scale (Subjective Norm Scale) having the biggest item pool (15). The relevant literature state that 10 participants per item yield good result (Worthington & Whittaker, 2006). These participants were determined through convenience sampling technique. The 95 of the participants (63.33%) were male while the 55 (36.66%) were female. The age of participants was collected as a categorical variable. 34 participants were between 18 and 20 years old, 69 were between 21 and 23 years old, 29 were between 24 and 26 years old, and 18 were 26 years old or above. In the second step which is the testing of the proposed model, the data were collected from a

Curr Psychol Fig. 2 The proposed model

Internet anxiety

Posive atude

Negave atude

Subjecve norm

Intenon of receiving online counseling

Behavior of receiving online counseling

Perceived behavioral control

total of 480 students [319 (66.46%) female, 161 (33.54%) male] studying at faculty of education of the same university, but they are different from the participants in the first step. The age of participants also was collected as a categorical variable. 85 participants were between 18 and 20 years old, 316 were between 21 and 23 years old, and 79 were between 24 and 26 years old. The distribution of the sample can be seen in Table 1. Data Collection Tools In this study, four different data collection tools were developed to measure subjective norm about the online counseling, perceived behavioral control, intention and behavior. Formerly developed tools were used to measure the attitude towards online counseling and internet anxiety. Item pool was created during the development of the scales. Four item pools, composed of 15, 11, 8 and 9 items were developed for subjective norm scale, perceived behavioral control, intention, and behavior, respectively. The opinions of two specialists with PhD, who have researches on educational psychology and development of scales, were asked about the content validity of the items, language, and suitability of the items for the developmental level of the target group. With reference to feedbacks, only formal arrangements were made but no item was removed. In accordance with the feedbacks, the items were revised. These revisions mostly aimed at improving the linguistic quality of items so that the Table 1

Gender Age

Distribution of Samples

Male Female 18–20 21–23 24–26 26 and above

Sample for scale development

Sample for model

95 55 34 69 29 18

161 319 85 316 0 79

participants could easily comprehend them. Moreover, experts stated that two of the items which were supposed to be about the intention actually measured behavior. With reference to this feedback, these two items were revised so that they would measure the intention. Also, they expressed that two items measuring behavior were incoherent. These items were revised, as well. After the revisions, no feedback was received from different experts. All of the items in item pool were conducted, and the factor analysis was carried out. Factor analyses were conducted in order to test the construct validity of the scales. The suitability of the data for the factor analyses was examined through Kaiser Mayer Olkin (KMO) and Bartlett’s Sphericity tests. KMO findings of three scales were above .60, which is the cutoff value of acceptable level, and ranged between.71 and .91. Moreover, all Chisquare values obtained from Bartlett’s sphericity test demonstrated significance at the level of p < .01, which means that the data are suitable for factor analysis (Kline, 2000). Afterwards, exploratory factor analysis based on principle components method was conducted on a total of 43 items, which were in four scales. 13 items were excluded from the scales because of a variety of reasons such as factor loadings below .30 or overlaps (overlapping items had factor loadings above .30 in more than one factors and the difference between these factor loadings was below .10). In the final models, factor eigenvalues and scatter plots indicated single-factor constructs for all of the four scales. Evidences of construct validity and reliability of the developed scales are presented in Table 2. Factor eigenvalues of four scales were between 2.607–4.941 range. Variance ratios explained by the scales ranged between 43.44% and 31.76%, which are above 30%, acceptable limit for the singlefactor constructs (Çokluk et al., 2010). Factor loadings of all items in scales were above .30, which is the acceptable level (Hair et al., 2006). Communalities of all items ranged between .20 and .83. All these values indicate the power of the scales. When the reliability values were examined, it was observed that the corrected item-total correlations and Cronbach α internal consistency coefficients ranged between .35–.77 and .73–.91, respectively. These values indicate the quality of the

Curr Psychol Table 2

Evidences of validity and reliability of the developed scales Total variance explained

Cronbach α

Factor Communalities Corrected loadings item-total correlation

Item discrimination index (t)

sn6: the culture I live in doesn’t find online counseling strange. sn5:

.804

.646

.36–.64

6.05***-10.43*** %43.44

.73

.691

.477

sn1: sn3:

.642 .626

.412 .392

.35–.68

5.32***-15.07*** %42.13

.80

.51–.77

7.96***-14.55*** %61.76

.91

.35–.66

5.17***-12.35*** %46.00

.85

Subscales and items

Subjective norm

sn4:

.622

.386

.541

.293

ad5: I don’t feel pressured about receiving online counseling. .799 ad7: .763

.639 .583

ad8: ad1:

.719 .673

.516 .453

ad3: ad6: ad2:

.599 .573 .510

.358 .329 .260

ad4: My computer knowledge is enough to receive online .481 counseling at any time. Intention n5: I foresee that I will certainly receive online counseling in .838 the future. n2: .827

.231

sn2: I would like to try receiving online counseling at least once. Perceived behavior control

.702 .684

n6: n7: n4:

.827 .814 .813

.684 .663 .661

n8: n1:

.797 .748

.635 .559

.594

.352

.765

.589

.748 .733 .710 .699 .688 .649 .647 .444

.559 .537 .504 .488 .473 .421 .419 .197

n3: I can receive online counseling when I have psychological issues. Behavior d6: I can express myself freely in an online counseling session. d3: d9: d4: d5: d7: d1: d8: d2: Online counseling makes the psychological counseling interesting. ***

p = .00

model by being above the acceptable levels (Çokluk et al., 2010; Hair et al., 2006). Item discrimination indices showed that the items discriminated the participants at the level of p = .00. As a results of the analyses, all of the scales were 5-point Likert-types, and Online Counseling Subjective Norm Scale,

Online Counseling Perceived Behavioral Control Scale, Online Counseling Intention Scale, and Online Counseling Behavior Scale were composed of 6, 8, 8, and 9 items, respectively. The participants can chose from strongly disagree to strongly agree. The higher scores obtained from scales indicate the higher degrees of the measured characteristic.

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Online Counseling Attitude Scale Developed by Rochlen et al. (2004) and adapted into Turkish by Demirci et al. (2014), this scale is 6-point Likert-type and composed of 10 items and two factors [Value of Online Counseling (5 items) and Discomfort with Online Counseling (5 items)]. Evidences of construct validity indicated good fit with the original scale(GFI = .91, RMSEA = .056,SRMR = .071, NFI = .94,CFI = .96,IFI = .96, RFI = .92). When the evidences of reliability were examined, it was observed that Cronbach α internal consistency coefficients were calculated to be .84 for Value of Online Counseling and .80 for Discomfort with Online Counseling. Moreover, corrected item-total correlations ranged from .59 to .70 for Value of Online Counseling and from .50 to .70 for Discomfort with Online Counseling. Internet Anxiety Scale Developed by Joiner et al. (2007) and adapted into Turkish by Akın (2012) to measure the internet anxiety, this scale is 5-point Likert-type and composed of 6 items. The scores obtained from these two factors aren’t allowed to be summed up. However, the scores are used separately as different scales. The highest score that can be obtained from internet anxiety scale is 30 and the lowest score is 6. Items 3 and 4 are reverse. Values of goodness of fit about the construct validity are presented below: Internet Anxiety X 2 = 15.11, Chi Square/df = 1.89, p = 0.056, GFI = .98, and AGFI = .96, RMSEA = .054, NFI = .97, CFI = .98, IFI = .98, RFI = .94. Cronbach α internal consistency coefficient was .69 and corrected item-total correlations ranged from .20 to .56.

Table 3

Goodness of fit indices and the acceptable threshold ranges

Index

Obtained Acceptable value threshold range

X2 p

16.27 .003

≥.05 (Hair et al., 2006).

X2/df GFI

4.06

≤5 (Sümer, 2000; Marsh and Hocevar, 1988).

.99

≥.90 (Hair et al., 2006).

AGFI

.93

≥.90 (Hair et al., 2006; Maccallum & Hong, 1997).

RMSEA .08

≤.08(Hair et al., 2006; Browne & Cudeck, 1993).

SRMR

.03

≤.08(Tabachnick & Fidell, 2007; Hair et al., 2006).

NFI NNFI

.99 .95

CFI

.99

≥.90 (Bentler & Bonett, 1980). ≥.90 (Vidaman & Thompson, 2003; Bentler&Bonett, 1980). ≥.90 (Vidaman & Thompson, 2003; Bentler, 1990).

IFI

.99

≥.90(Bollen, 1989).

PNFI

.20

>.50 (Mulaik et al., 1989).

acceptable fit (Marsh & Hocevar, 1988). GFI value strongly supports the model fit. Other absolute fit indices such as AGFI, RMSEA and SRMR indicate a good fit. When the incremental fit indices are examined, a similar high level of fit can be observed. In this group, NFI, CFI and IFI values are very close to 1. All of these indicators point at a strong fit between the expected and observed models. In other words, they show that the obtained data confirmed the proposed model. The only index that failed to yield a good value among goodness of fit indices is the PNFI, which belongs to the parsimonious index group. This situation indicates a low simplicity for the model.

Analysis Path Analyses The proposed model was tested through a structural equation model based on maximum likelihood method using LISREL v.8.71 software. Goodness of fit indices were examined in the evaluation of model’s fit. Path analyses and path coefficients obtained from these analyses (β), t-values, determination coefficients (R2), and error variances (e) were used for testing the research hypotheses.

Findings Model Fit Goodness of fit indices and the thresholds for these values are presented in Table 3. X2/dfratio of the model is below 5. When we take the sample size into account, this ratio can be considered to indicate an

The results of path analyses show that the majority of research hypotheses are confirmed. All of the paths except for H4 are statistically significant. Accordingly, path coefficients of hypotheses are presented below: H1: Positive attitudes towards receiving online counseling have a positive and significant impact on the intention of receiving online counseling(β = .30; t = 7.61; p < .01). H2: Negative attitudes towards receiving online counseling have a negative and significant impact on the intention of receiving online counseling (β = −.07; t = 2.30; p < .05). H3: Subjective norms about receiving online counseling have a positive and significant impact on the intention of receiving online counseling (β = .25; t = 6.41; p < .01).

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H4: Perceived behavioral control about receiving online counseling has no significant impact on the intention of receiving online counseling (β = −.04; t = 1.04; p > .05). H5: Perceived behavioral control about receiving online counseling has a positive and significant impact on the behavior of receiving online counseling (β = .13; t = 2.76; p < .01). H6: Internet anxiety has a negative and significant impact on the behavior of receiving online counseling (β = −.35; t = 8.97; p < .01). H7: The intention of receiving online counseling has a positive and significant impact on the behavior of receiving online counseling (β = .19; t = 4.11; p < .01).

to the counseling sessions, materials and questionnaires that the client can interact independent from the counselor, or the tools used to upload homework/products that are prepared by the client. Morris (2014) argues that online clients can effectively benefit from the system only after they are taught how to utilize the opportunities provided by online counseling system by the counselor. The second one is related to the security level provided by the online counseling system. The clients upload their personal information and personal products to online counseling systems, and audio and video recordings of the sessions are kept in these environments. Privacy and security measures about all these factors are generally under the counselor’s responsibility (Morris 2014). Therefore, it can be considered that uncertainties about privacy and security may create an anxiety towards the security of online counseling process and affect the tendency to use it. In their research, Mehta et al. (2015) emphasize that the clients’ written expression and social skills are determinative in terms of making use of online counseling. From this viewpoint, selfexpression/reflection and social interaction skills in online settings can be considered as other anxiety factors that affect the intention of receiving online counseling. Subjective norm and positive attitude are the main elements that have an impact on intention. When these two impacts are considered within the scope of internet anxiety, it is possible for these two elements to have an impact on internet anxiety although it wasn’t focused on in this study. The future study can focus on this impact. Other elements of the research are composed of positive attitudes towards online counseling, subjective norms and negative attitudes. In contrast with the argument of TPB, perceived behavioral control has no impact on intention, but has a direct and significant impact on behavior. According to the model, the behavior of receiving online counseling is affected firstly by intention and then by perceived behavioral control in the order of effect size. Still, it is difficult to state that either intention or perceived behavioral control has a profound influence on the behavior of receiving online counseling.

The structural equation model and the standard coefficients obtained as a result of the analyses are presented in Fig. 3.

Discussion and Conclusion This research attempted to explain the reasons behind university students’ behaviors of receiving online counseling based on Ajzen’s (2006) TPB. In accordance with this, a model was proposed to investigate the causal relationships among attitudes, subjective norm, perceived behavioral control about receiving online counseling, internet anxiety, intention and behaviors of receiving online counseling. The proposed model was tested through a structural equation model. According to the results, the proposed model estimated the variance on the intention and behavior of receiving online counseling. When the model was examined, it was observed that the variance on the intention of receiving online counseling was affected by the internet anxiety most. Similarly, the prominent researches provide findings which support the idea that anxiety towards online environments is an important obstacle to benefit from online counseling (Mehta et al. 2015; Morris 2014). The first type of anxiety involves online counseling systems, documents that the clients can download in addition Fig. 3 Causal model of university students’ behaviors of receiving online counseling and standard coefficients

Anxiety towards using internet

Posive atude

-.35 .30

Negave atude

-.07 İntenon of receiving online counseling

.25 Subjecve norm

.04 Perceived behavioral control

.13

.19

Behavior of receiving online counseling

Curr Psychol

Although it is observed in the literature that the individuals state that they may need online counseling (Lunt, 2004) and seek help by maintaining privacy (Young, 2005), it was determined in this study that clients’ intentions and locus of behavioral control perceptions don’t have an impact on the behavior of receiving online counseling. At this point, the investigation of elements such as clients’ socio-cultural backgrounds or the environment where the client-counselor interaction takes place can be beneficial since these variables have an effect on intention-behavior relationship. Along with this, although intention has a low impact, positive attitude and subjective norm are the main elements that have an influence on this low impact. Therefore, when the individuals intent on receiving online psychological counseling, whether they have a positive attitude towards this behavior or not and the judgements of their environment about this behavior are the two elements that have the highest impact. As a result, if the privacy is ensured, it is considered that the number of people receiving online counseling will increase. It can be recommended for the future studies to focus on the relationship between the privacy and receiving online counseling. Ultimately, the results show that the most important predictor of the intention of receiving online counseling is the positive attitude towards receiving online counseling while the most important obstacle is the internet anxiety. There are a limited number of studies about this issue in Turkey. One of them is the study conducted by Zeren (2015). In her study, Zeren (2015) stated that the clients felt comfortable and contended in online counseling. Actually, if the individuals having the intention of receiving online counseling can learn how to cope with their internet anxiety, there can be an increase in their behavior of receiving online counseling. Other studies showed that online counseling is at least as productive and pleasing as face-to-face counseling (Cook & Doyle, 2002; Murphy et al., 2009; Kilroe, 2010a, b; Brown, 2012). Receiving counseling is worrying by itself. Another result of this study is that the intention and behavior of participants about receiving online counseling is positive. This situation is promising since it means that the individuals will be willing to receive online counseling when this service becomes widespread. Therefore, the increase in the online counseling services provided by universities as a part of their medico-social services will facilitate providing the student personal services as a requirement of contemporary educational approach and play a supporting role for individuals to cope with their problems. Moreover, it can also be considered as a beneficial psychological service for high schoolers to deal with their turbulent period. In conclusion, this study shows experts and researchers that the need of online counseling is a reality. Shapiro and Schulman (1996) mention the presence of a new generation who was born into novel technologies, has grown up with computers and has been benefiting from all of these opportunities. Therefore, it is considered that even if this new generation doesn’t have an intention of seeking such help today, this generation will need these

services in the near future. In conclusion, the experts in this field are recommended to focus on studies which will set up the infrastructure of these services and minimize the security risks. This field is new in Turkey. The experts both in psychology and counseling should be trained for online counseling, and the courses about online counseling should take place in the curriculums of these fields. When the curriculums of universities were examined, it was observed that no course about online counseling was present (e.g. http://llp.marmara.edu.tr; http://akts.hacettepe.edu.tr/). At least, the course of online counseling can take place in curriculum as an elective course. Moreover, the experts graduated from the mentioned programs can be provided with in-service training. The researchers are recommended to study further by adding different variables. When it is considered that this kind of services will become widespread, it can be recommended that the focus should be on the counseling process in future studies. Especially some topics such as therapeutic cooperation, resistance, conveying empathy, and self-revelation of the client can bring some novel viewpoints to the research. Along with this, studies comparing counseling through chat/e-mail, video counseling, and voice counseling are recommended to be conducted. Thus, the most efficient method can be determined, and such studies can facilitate acceptance of online counseling in the field. Moreover, the participants of this study were the individuals who aren’t counselors. In future studies, it is recommended to work with counselors or counselor candidates. Therefore, determining the perceptions of counselors about online counseling would reveal the opinions of counselors about the necessity or efficacy of such a service. Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. Ethical Approval Informed consent was obtained from all individual participants included in the study.

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