Acceptance of E-mental health interventions and its determinants among psychotherapists-in-training during the first phase of COVID-19

Staeck, Robert; Drüge, Marie; Albisser, Stefan; Watzke, Birgit

doi:10.1016/j.invent.2022.100555

Cited by 4 publications

(9 citation statements)

References 61 publications

(93 reference statements)

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“…The number of distinct classes is not defined a priori but is chosen based on statistical criteria ( 22 ). In contrast to previous research using the same dataset ( 14 , 17 ), which mainly focused on the determinants of EMH and interaction effects, LCA can provide insight into latent subgroups that may be present in the current sample but have not yet been explored. These classes could help researchers and practitioners understand differences and similarities between groups, with implications for future research and the development of tools to foster EMH acceptance.…”

Section: Introductionmentioning

confidence: 94%

“…Acceptance varied significantly between modalities (e.g., videoconferencing vs. unguided programs; cf. 13 , 14 ). Also, UTAUT has been used in many studies which consider the perspective of the client ( 15 , 16 ) as well as the perspective of the medical/psychological staff ( 12 , 14 , 17 ).…”

Section: Introductionmentioning

confidence: 99%

“… 13 , 14 ). Also, UTAUT has been used in many studies which consider the perspective of the client ( 15 , 16 ) as well as the perspective of the medical/psychological staff ( 12 , 14 , 17 ). Therefore, the UTAUT holds particular relevance regarding the acceptance of EMH in a medical context ( 12 ) in different target groups.…”

Section: Introductionmentioning

confidence: 99%

“…This bears relevance as the acceptance of EMH among PiT could influence the future of healthcare systems. However, to date, research on this specific group has been scarce, with only two studies utilizing the same dataset as the present study being published ( 14 , 17 ): The overall acceptance of EMH among PiT, which was assessed on a 1-5 Likert scale and then categorized into the categories low (1–2.34), moderate (2.35–3.67), or high (3.68–5), can be described as moderate in N = 216 German-speaking PiT ( 14 ). This research also highlights the fact that Performance Expectancy, Social Influence and concerns about the therapeutic alliance determine EMH acceptance.…”

Section: Introductionmentioning

confidence: 99%

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Exploring subgroups of acceptance prediction for e-mental health among psychotherapists-in-training: a latent class analysis

Staeck,

Stüble,

Drüge

2024

Front. Psychiatry

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Theoretical backgroundResearch of E-Mental Health (EMH) interventions remains a much-studied topic, as does its acceptance in different professional groups as psychotherapists-in-training (PiT). Acceptance among clinicians may vary and depend on several factors, including the characteristics of different EMH services and applications. Therefore, the aims of this study were to investigate the factors that predict acceptance of EMH among a sample of PiT using a latent class analysis. The study will 1) determine how many acceptance prediction classes can be distinguished and 2) describe classes and differences between classes based on their characteristics.MethodsA secondary analysis of a cross-sectional online survey was conducted. N = 216 PiT (88.4% female) participated. In the study, participants were asked to rate their acceptance of EMH, as operationalized by the Unified Theory of Acceptance and Use of Technology (UTAUT) model, along with its predictors, perceived barriers, perceived advantages and additional facilitators. Indicator variables for the LCA were eight items measuring the UTAUT-predictors.ResultsBest model fit emerged for a two-class solution; the first class showed high levels on all UTAUT-predictors, the second class revealed moderate levels on the UTAUT-predictors.ConclusionThis study was able to show that two classes of individuals can be identified based on the UTAUT-predictors. Differences between the classes regarding Performance Expectancy and Effort Expectancy were found. Interestingly, the two classes differed in theoretical orientation but not in age or gender. Latent class analysis could help to identify subgroups and possible starting points to foster acceptance of EMH.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exploring subgroups of acceptance prediction for e-mental health among psychotherapists-in-training: a latent class analysis

Staeck,

Stüble,

Drüge

2024

Front. Psychiatry

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“…There is ample evidence supporting psychological outcomes that are widely circulated on the internet with negative news results due to the COVID-19 pandemic (Brooks et al, 2020). Of course, we must not give up until here to the conditions that have occurred due to the impact of the virus (Staeck et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Challenges of Training Institutions in Accelerating The Availability of Graphic Design Online Classes for Trainees

2022

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The digital era is currently affecting activities in the world of training. This study investigates the challenges training institutions face in accelerating the availability of online classes for today's trainees. This research uses a descriptive qualitative approach. A total of 126 participants came from graphic design training participants. Then, the data collected in this study was by distributing a 4-scale questionnaire, pretest-posttest assessment, and using a Likert Scale observation sheet with five scales (0-4). The results showed that the participants had a reasonable opinion of the availability of online classes at training institutions on the aspects of mastery of the material by the instructor, the accuracy of the presentation, the relevance of the training content, and its suitability for the needs of the training participants. The significance value based on age range, gender, and graduate status is 0.863, 0.094, and 0.107. The results of the pretest-posttest assessment also increased when using online classes. Positive results also impact training participants in understanding graphic design material as a whole with the availability of online courses at training institutions. The presence of this online class has had many positive influences in all aspects but still needs improvement because there are challenges that need to be resolved by the Training Institute. The faster the availability of online classes at the Training Institute, the quicker the fulfillment of training needs.

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Mental Health Professionals' Views on Providing Online Counseling within the Scope of UTAUT Model: A Q Method Analysis

Erus,

Çanakçı Uğur

2024

Cukurova University Faculty of Education Journal

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Online counseling, an intervention that has evolved alongside technological advancements and become integrated into individuals' lives, has gained even more popularity. At this point, it is essential to investigate the acceptance and usage of online counseling by mental health professionals. This research was conducted with 35 mental health professionals (psychologists and counsellors) who provide both online and face-to-face counseling. In the study, Q methodology was used to better understand the subjective thoughts, attitudes, and beliefs of participants to understand their behaviors regarding the acceptance and use of online counseling according to the UTAUT model. As a result of the research, it was found that factors related to the acceptance and usage of online counseling were grouped into two factors for mental health professionals. The research findings indicate that mental health professionals are grouped into two factors regarding factors related to the acceptance and utilization of online counseling. It has been observed that performance expectations and facilitating conditions influence the acceptance and utilization of online counseling for participants in Factor 1, while effort expectations and facilitating conditions influence the behavior of acceptance and utilization for participants in Factor 2. Additionally, it was found that mental health professionals in Factor 1 have a more positive attitude towards online counseling, whereas those in the second group prefer face-to-face counseling over online counseling.

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Acceptance of E-mental health interventions and its determinants among psychotherapists-in-training during the first phase of COVID-19

Cited by 4 publications

References 61 publications

Exploring subgroups of acceptance prediction for e-mental health among psychotherapists-in-training: a latent class analysis

Exploring subgroups of acceptance prediction for e-mental health among psychotherapists-in-training: a latent class analysis

Challenges of Training Institutions in Accelerating The Availability of Graphic Design Online Classes for Trainees

Mental Health Professionals' Views on Providing Online Counseling within the Scope of UTAUT Model: A Q Method Analysis

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