Abstract
Introduction
Adjustment disorder (AjD) is a maladaptive response to one or more psychosocial stressors. In many cases, the symptomatology of this disorder disappears once the stressor or its consequences are no longer present. However, in some cases, if left untreated, the symptoms may worsen and develop into a more severe mental disorder. In this regard, different authors propose that a low-intensity intervention may be suitable for this disorder. Previous studies with other mental disorders and with patients with AjD found that blended interventions can be a viable and effective option. The aim of this study is to analyze the feasibility (the participants' expectations and preferences, the satisfaction and acceptance, the appropriateness of different methods of recruitment and data collection, and the reasons for dropping out) of a blended cognitive-behavioral intervention (CBT) for AjD that combines the use of a self-applied Internet-based program with videoconference sessions with a therapist. As a secondary objective, the potential efficacy of this intervention will be tested.
Method and analysis
A feasibility trial with a single-group and open-trial design will be conducted. A total of 41 participants will be assigned to the single treatment group. All the participants will be assessed for eligibility and respond at four measurement points: pre-treatment, post-treatment, and 3- and 12-month follow-ups. The treatment combines the use of an Internet-based intervention through a web platform with videoconference sessions with a therapist every 10–12 days. The intervention contains seven modules and is based on CBT. The main outcome measures are related to the feasibility of the intervention (adherence, treatment satisfaction and expectations, participants' opinions, preferences, therapeutic alliance, and usability). Clinical measures will also be assessed.
Discussion
To the best of our knowledge, this is the first study to test a blended intervention for AjD in the Spanish language. We expect this intervention to be feasible, and that a future Randomized Controlled Trial will be able to show its efficacy. Potential limitations include difficulties in recruiting the sample, failures in the computer systems, or a high dropout rate. Measures have been taken to try to reduce the impact of these limitations. This study received the approval of the Ethics committee of Universitat Jaume I in March 2022 (CD/42/2022).
Trial registration
ClinicalTrials.gov Identifier: NCT05464121. Registered 19 July 2022, https://clinicaltrials.gov/ct2/show/NCT05464121.
Keywords: Adjustment disorder, Psychological treatment, Blended psychotherapy, Cognitive behavioral therapy, Videoconference
Highlights
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Blended interventions for adjustment disorder could be a suitable alternative to self-applied or face-to-face treatments.
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The blended format described in this study could improve adherence to treatment.
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The feasibility results will be key to future Randomised Controlled Trials.
1. Introduction
Adjustment disorder (AjD) is a stress-related disorder defined as a maladaptive response to one or more identifiable psychosocial stressors. Its definition and diagnostic criteria are included in two of the most widely used diagnostic manuals: the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) of the American Psychiatric Association (APA, 2013) and the International Classification of Diseases (ICD-11) of the World Health Organization (WHO, 2018). However, the DSM-5 and previous versions of the ICD have received multiple criticisms that have led to this disorder being under-researched (Zelviene and Kazlauskas, 2018). In its latest version, the ICD-11 attempted to overcome the barriers observed in the DSM and previous versions of the ICD by incorporating a new definition of AjD with specific symptom criteria.
The ICD-11 diagnostic criteria for AjD include: (a) Presence of an identifiable psychosocial stressor or multiple stressors, (b) symptoms of worry related to the stressful event or the implications of the stressor, (c) a failure to adapt to the stressor causing significant impairment, (d) symptoms usually emerge within one month of the stressor and resolve within 6 months, unless the stressor persists for a longer period, and (e) AjD cannot be diagnosed if criteria for any other mental disorder are met.
One important aspect to consider is the high prevalence of this disorder (Zelviene and Kazlauskas, 2018), which is especially serious due to the lack of accessibility to psychological treatments for mental disorders in general. More than 60 % of people in need of psychological help cannot access treatment (Wang et al., 2005). Therefore, it seems urgent to develop new ways to deliver treatments that can increase their accessibility (Kazdin, 2017).
In the specific case of AjD, some authors suggest that despite being a frequent diagnosis, patients with AjD yet often remain untreated (Bachem and Maercker, 2016). One reason for this is that, due to the lack of clarity so far in diagnostic criteria, there is little clinical research focused on analyzing the treatment of this disorder (Bachem and Casey, 2018; O'Donnell et al., 2019). Literature reviews that focused on studying psychological treatments for AjD comprehensively, suggest that among the variety of interventions, Cognitive Behavioral Therapy (CBT) stands out as one of the most widely used (Constantin et al., 2020; Domhardt and Baumeister, 2018; O'Donnell et al., 2018). However, the study by O'Donnell et al. (2018), which is the only one that included a formal quality assessment, highlighted the low quality of the studies conducted so far. All other reviews agree on the need for further research on this issue.
It is suggested that low-intensity interventions, such as self-applied ones, may be more appropriate than traditional face-to-face treatment for AjD due to its transient nature (Bachem and Casey, 2018). Moreover, this format could help to increase the dissemination of psychological treatment and it could be as effective as face-to-face format, although further research is needed (e.g., Hedman-Lagerlöf et al., 2023).
This is supported by previous studies testing self-applied interventions for AjD that showed that this format is effective in reducing AjD symptomatology (e.g., Eimontas et al., 2018a; Eimontas et al., 2018b; Moser et al., 2019). In the study by Moser et al. (2019), it is important to mention that the reduction in AjD symptoms was not significantly different between the Care as Usual (CAU) control group and the intervention group (CAU + online treatment). However, the intervention group did report a significant improvement in some secondary measures (less depressive symptomatology and higher quality of life). Another example is the recent meta-analysis by Svärdman et al. (2022). It focused on investigating the efficacy of Internet-delivered CBT (ICBT) in adults with elevated perceived stress or stress-related disorders (including AjD) and showed the efficacy of these interventions in reducing symptomatology associated with these disorders.
Despite being an effective format, one of the disadvantages of Internet-delivered interventions is the high number of dropouts. A qualitative study focused on analyzing the experiences of some participants with emotional disorders who dropped out of an online transdiagnostic treatment showed that the lack of interaction with a therapist and the lack of personalization of the treatment were two of the main reasons for dropping out (Fernández-Álvarez et al., 2017).
In the case of AjD, an example of ICBT is described in the study of Rachyla et al. (2020). A Randomized Controlled Trial (RCT) was conducted with the aim of testing the efficacy of an ICBT called TAO compared to a waiting list control group. The results provided evidence for the efficacy of this intervention in reducing the impact of AjD. However, the dropout rate reported was around 23.5 %. Although this figure is lower than what has been observed in other studies (e.g., Eimontas et al., 2018a), it is still high. The authors suggest that incorporating therapeutic support through phone calls might have improved adherence to treatment. Nevertheless, it is necessary to continue to develop strategies to reduce the number of dropouts from these types of interventions.
One of the alternatives that can help to overcome these limitations is blended format, which is defined as the combination of self-applied interventions with face-to-face sessions with a therapist (Erbe et al., 2017). Some authors propose that sessions with the therapist do not necessarily have to be in person, but rather they can be delivered in other formats such as videoconferencing (e.g., Schuster et al., 2022). The possibility of delivering the entire intervention online could allow a larger number of people to access the treatment.
It is also suggested that blended format allows for greater therapist support and personalization of treatment which helps to reduce dropouts (Rasing et al., 2020). A recent literature review of computerized and blended treatments for depression, estimated that the dropout rate in unguided CBT ranged from 0 to 21 %, in guided CBT treatments it was around 17 %, and in blended CBT interventions it ranged from 0 to 13 % (Rasing et al., 2020).
Moreover, previous studies conducted with other mental disorders have shown that blended interventions are a well-accepted and effective option (e.g., Erbe et al., 2017; Schuster et al., 2018). Additionally, this format can also make treatment more cost-effective by reducing the time with the therapist and, therefore, the treatment costs (Erbe et al., 2017). Some authors, such as Díaz-García et al. (2021), suggest that this format may be suitable for participants who do not respond well to fully self-applied or fully guided treatments or prefer a format that combines these two.
To the best of our knowledge, only one blended treatment for AjD has been proposed so far. This CBT intervention was tested in an RCT and only included participants with the anxious subtype of AjD (Leterme et al., 2020). It combined a computer-based treatment consisting of five modules with face-to-face sessions with a professional. The results of this study showed that blended CBT was as effective as face-to-face format in reducing anxiety, depression, worry and perceived stress. However, in the secondary analysis blended CBT was slightly more effective in reducing some secondary outcomes related to anxiety and depression, compared to a face-to-face CBT group and a waiting list control group.
Therefore, the primary aim of this study is to analyze the feasibility of a CBT blended intervention for AjD as defined in the ICD-11. To this end, the use of a web platform will be combined with videoconference sessions with a therapist. The specific objectives are: (1) to explore participants' expectations and preferences, (2) to assess patients' satisfaction and acceptance of the treatment, (3) to study the appropriateness of different methods of recruitment and data collection (e.g., whether we can reach the target population, how broad or restrictive the eligibility criteria are, how willing patients are to participate, time needed to collect data), and (4) to explore participants' reasons for non-participation and dropping out of the treatment. Additionally, as a secondary objective, the potential efficacy of this intervention at post-treatment and follow-ups will be tested. For this purpose, intra-group changes in AjD related symptoms from baseline to post-treatment and follow-ups will be analyzed, with the main comparison being between baseline and post-treatment. The inclusion of the two follow-ups will serve to analyze their viability for a future RCT.
2. Material and methods
2.1. Design
A feasibility trial with a single-group and open-trial design will be conducted. It will include four measurement points: baseline (pre-treatment), immediately after the intervention (post-treatment), and at the 3- and 12-month follow-ups.
This work was registered in the Clinical Trials database (https://clinicaltrials.gov/) prior to its initiation (NCT05464121) and received the approval of the Ethics committee of the Universitat Jaume I (Castellón, Spain). The extension of the Consolidated Standards of Reporting Trials (CONSORT) statement for pilot and feasibility studies (Eldridge et al., 2016), the Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and online TeleHealth guidelines (Eysenbach, 2011), and the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines (Chan et al., 2013a; Chan et al., 2013b) will be followed.
2.2. Study setting
This study will be conducted at the Emotional Disorders Clinical at the Universitat Jaume I in Castellón (Spain), although the entire intervention will be administered online.
2.3. Eligibility criteria
Participants will be included in the study if they meet the following criteria: (a) age > 18 years, (b) meeting diagnostic criteria for AjD based on the ICD-11 definition, (c) exceeding the cut-off point of 47.5 on the ADNM-20 questionnaire (Lorenz et al., 2016), (d) signing the informed consent, (e) being able to understand and read Spanish, (f) being able to use a computer and having access to the Internet, and (g) having an email address.
Reasons for exclusion include risk of suicide or self-destructive behaviors, diagnosis of another serious mental disorder (substance abuse or dependence, psychotic disorder, dementia, bipolar disorder, or personality disorder), receiving another psychological treatment during the study for AjD, or experiencing an increase and/or change in medication during the study period.
2.4. Intervention
2.4.1. Internet self-applied intervention and videoconference sessions
The blended intervention will combine a self-applied program administered through a web platform and videoconference sessions with a therapist using Google Meet software.
The TAO self-applied program (Adjustment Disorder Online) is accessible online through the Psychology and Technology website. Data security and protection issues can be found in the Ethics and dissemination section. All participants will have their own username and password that will give them access to the platform at any time. The platform contains text, downloadable PDFs, and various multimedia contents such as images and videos. It also offers the possibility of reviewing previously viewed treatment content, and it includes a calendar and graphs with clinical measures that allow participants to monitor their progress after treatment and during the follow-ups. To ensure the safety of the participants, the platform includes alarms that alert the clinician when a participant may be at risk of suicide. A screenshot of the treatment platform can be seen in Fig. 1.
Fig. 1.
Image of the treatment web platform.
The content of the program is organized in seven sequentially accessible modules, each lasting approximately 60 min. The estimated duration of the intervention is 12 weeks. Thus, participants will complete one module of the treatment every 10–12 days, in addition to having an individual videoconference session with a therapist (lasting approximately 30 min). The aim of these sessions will be to present the main contents of the module to be worked on online in the next few days, resolve doubts, and motivate the patients to continue with the therapy.
To improve adherence to the intervention during treatment and follow-ups, participants will receive reminder emails. Criteria for discontinuing the intervention will be a change in the dosage of the psychotropic drug, the explicit request of the participant, or a worsening of the mental disorder. A participant will be considered a treatment dropout when, after meeting the eligibility criteria and signing the informed consent, they explicitly declare that they do not want to continue with treatment or when they have not responded to reminders for videoconference sessions or access to the platform for 1 month.
The therapists who will participate in the study, during both the assessment and treatment process, will be trained clinicians with at least a master's degree and training in CBT protocols.
2.4.2. Therapeutic components
This treatment is the optimized version of the original intervention protocol for AjD developed by Botella et al. (2008) and subsequently updated by Rachyla et al. (2020). It is based on CBT and includes different components of positive psychology and exercises adapted from Neimeyer's (2000) reconstruction of meaning approach to grief therapy. A detailed description of the treatment content can be found in Table 1.
Table 1.
Videoconference sessions, modules, and objectives.
| Session | Videoconference session | Module | Objectives |
|---|---|---|---|
| S0 | 10 min:
20 min:
|
M0. Starting this program |
|
| S1 | 10 min:
20 min:
|
M1. Understanding emotional reactions |
|
| S2 | 10 min:
20 min:
|
M2. Learning to cope with negative emotions |
|
| S3 | 10 min:
20 min:
|
M3. Accepting the problems |
|
| S4 | 10 min:
20 min:
|
M4. Learning from problems |
|
| S5 | 10 min:
20 min:
|
M5. Changing the meaning of the problems |
|
| S6 | 10 min:
20 min:
|
M6. Relapse prevention |
|
2.5. Outcome measures
The assessment will take place at four time points: pre-treatment, post-intervention, at the 3-month and 12-month follow-ups (see a detailed description of the assessment procedure in Table 2).
Table 2.
Measures, times, and tools for assessment.
2.5.1. Sociodemographic data, screening and diagnostic measures
First, a brief structured telephone interview and a semi-structured videoconference interview developed for this research team will be used to check the inclusion/exclusion criteria. The age, gender, educational level, occupation, marital status, and place of residence of all participants will be assessed.
For the diagnosis of AjD following the ICD-11 criteria, the ADNM-20 (Einsle et al., 2010) will be administered by a clinician via videoconference. It consists of a first part that includes a list of stressful events that participants may have experienced in the past 2 years. In the second part, patients' symptomatology is evaluated in reference to the most stressful event. The response scale ranges from 1 (never) to 4 (frequently). A cut-off point of 47.5 is required to differentiate between people with low and high risk of AjD (Lorenz et al., 2016). Previous studies showed the good psychometric properties of this questionnaire (Einsle et al., 2010).
Additionally, to ensure that the exclusion criteria are met and make a differential diagnosis, the corresponding modules of the Structured Clinical Interview for the DSM-IV (SCID-I; First et al., 1996) will be used mainly to rule out the diagnosis of major depression or posttraumatic stress disorder and the modules of Anxiety Disorders Interview Schedule (ADIS-IV; Brown et al., 1988) will be used mainly to rule out generalized anxiety disorder or other anxiety disorders.
2.5.2. Primary outcomes: feasibility assessment
2.5.2.1. Adherence
The number of modules completed by participants, the number of times participants enter the treatment, the total time spent in the treatment, whether they review the treatment contents, and the dropout rates will be recorded. The reasons for dropping out will be assessed using a qualitative interview designed by the clinical team of the study. This will include a list of reasons from which the person can choose why they dropped out of treatment (they can also add any that are not on the list), and questions about what they would have liked to have been different, whether they would have continued in the program if that had been different, what were the main barriers/limitations to treatment, and whether they can think of any strategies to improve adherence.
2.5.2.2. The expectations and satisfaction questionnaire adapted from Borkovec and Nau (1972)
It includes two different scales containing 6 items each (rated from 0 to 10). One refers to expectations about the treatment before the intervention begins. The other scale is used to assess satisfaction with the treatment once it is over.
2.5.2.3. The intervention opinion questionnaire
This opinion assessment tool was developed for this study. First, participants' preferences before and after the blended intervention will be assessed. Second, at post-treatment, participants will answer questions related to the satisfaction (0−10) and usefulness (0–10) of each component of the treatment, the different aspects of the intervention (e.g., text, videos, images), the videoconference sessions with a therapist every 10–12 days, and the blended format. Participants will be asked about the reasons for their scores, and the presence of adverse or unexpected events during treatment will be reported. Finally, the satisfaction and usefulness of each treatment module and the participants' opinions after each videoconference session with the therapist will also be evaluated using a response scale from 0 to 10.
2.5.2.4. The Working Alliance Inventory for guided Internet Interventions (WAI-I; Gómez-Penedo et al., 2020)
The WAI-I evaluates the components of the therapeutic alliance according to Bordin (1979), using 12 items assessed from 1 to 7.
2.5.2.5. The Usability System Scale (SUS; Bangor et al., 2008; Brooke, 1996; Castilla et al., 2023)
This instrument will be used to evaluate the usability of the TAO web platform. It has 10 items (rated from 1 to 5) and assesses the usability of a service or product and its acceptance by the users.
2.5.3. Secondary outcomes: preliminary efficacy assessment
The AjD symptomatology will be assessed using the Adjustment Disorder New Module-20 (ADNM-20; Einsle et al., 2010). The intensity with which a situation or a person lost as a result of the stressful event interferes with the participant's life will be evaluated with the Loss and Stress Inventory (IEP; Quero et al., 2019a). The Positive and Negative Affect Scale (PANAS trait; Díaz-García et al., 2020; Watson et al., 1988) will be used to assess two dimensions of mood (positive and negative affect). The Posttraumatic Growth Inventory (PTGI; Tedeschi and Calhoun, 1996; Weiss and Berger, 2006) assess positive psychological change after an adverse or traumatic experience. Finally, the Overall Anxiety Severity and Impairment Scale (OASIS; González-Robles et al., 2018; Norman et al., 2006) and the Overall Depression Severity and Impairment Scale (ODSIS; Bentley et al., 2014; Mira et al., 2019) will be used to assess the frequency and severity of anxiety and depression symptoms, as well as the degree of avoidance and interference. In the case of the ODSIS, an additional item was included to evaluate the presence of suicidal ideation symptoms.
2.5.4. Other outcomes
The change in efficacy measures after each treatment module will be assessed using questions related to the following aspects: mood at this time and changes in mood after the module, perceived self-efficacy in dealing with the stressful event, and acceptance and openness to future experiences. Additionally, the Purpose-in-Life Test-10 Items (PIL-10; Crumbaugh and Maholick, 1964; García-Alandete et al., 2013) and the Quality of Life Inventory (QLI; Frisch et al., 1992; Mezzich et al., 2000) will be used to assess different aspects of meaning in life and patients' quality of life in different areas and overall, respectively.
2.6. Sample size
Because this study is a feasibility trial, a formal sample size calculation is not required. However, for the potential efficacy objective, the sample size is determined by considering the changes in AjD symptoms between pre-test and post-test as the main outcome. To this end, a significance level of 5 % was assumed, with a statistical power of 80, a bilateral contrast, and an effect size of moderate magnitude (d = 0.50), according to Cohen's (1988) guideline for standardized mean differences. The resulting sample size was 34 participants. However, following a strict criterion an expected dropout rate of 17 % was considered (Rasing et al., 2020), resulting in a sample size of 41 participants.
2.7. Recruitment
Several social networks (e.g., Whatsapp, Instagram, Facebook, and Linkedin), informative posters placed on the Universitat Jaume I and Universitat de València campuses, the university websites, and traditional media (e.g., local newspapers and radio) will be used for recruitment. In addition, patients who seek psychological treatment at Universitat Jaume I Emotional Disorders Clinic will be recruited. Recruitment for this study is already ongoing. An example of the flowchart is shown in Fig. 2.
Fig. 2.
Flowchart of participants.
2.8. Data collection procedure
People interested in participating could contact the study by e-mail or telephone. The clinical team will respond to emails or calls within 24 h and set up an initial interview. After completing this first pre-screening interview by telephone, two assessment sessions will be held to confirm that the eligibility criteria are met. The Adjustment Disorder New Module-20 scale (ADNM-20; Einsle et al., 2010) will be used for the diagnosis of AjD according to the ICD-11. These sessions will be conducted via videoconference by a trained therapist. In addition, participants will be asked about their psychotropic medication and monitored for changes in dosage or type of medication during the treatment and follow-ups.
After participants have been informed of the characteristics of the intervention, they will sign an informed consent form and begin treatment. All of them will respond to assessments at four time points.
For participants who do not complete the intervention, they will still be encouraged to respond to T2, T3, and T4 assessments. Additionally, they will be asked to respond to the qualitative dropout interview.
2.9. Data analysis plan
The main data will be reported narratively for the primary feasibility objective, illustrated with descriptive statistics, and reported in accordance with the CONSORT 2010 declaration (Eldridge et al., 2016). Missing data will be used to determine dropout rates. Adherence will be evaluated based on the frequency with which each patient uses the program. Means (SD) and/or frequencies (%) will be used to portray the data in a descriptive manner.
For the secondary aim, mixed-effects models will be used to assess the treatment's potential efficacy of the treatment, as it allows intention-to-treat analyses. The pre-test, post-test, and two follow-ups (at 3 and 12 months) will be considered as measurement occasions. The effect sizes and associated 95 % confidence intervals (CI) for the intra-group changes will also be calculated. Both the completers and the intention-to-treat data will be subject to statistical analysis. SPSS version 28.0 will be used for all data analyses.
3. Ethics and dissemination
This study received the approval of the Ethics committee of the Universitat Jaume I in Castellón, Spain (file number CD/42/2022, March 2022). All the participants who will take part in the trial will receive a prior explanation of what the study will consist of and how the treatment works. After the explanation and before starting the intervention, all participants will sign an informed consent form that presents the study information in a detailed and clear manner. Patients will always participate on a voluntary basis and may leave the study at any time. The principles of the Declaration of Helsinki shall be fully respected throughout the trial. The treatment web platform, the software for videoconferencing, and the data collection-oriented web pages comply with the European Union data protection law. Participants will be provided with a personal username and password known only to them. The databases will use codes to protect sensitive data such as personal information, and personal data will be separated from clinical data. Only members of the study clinical team will have access to these data.
4. Discussion
The main aim of this study is to analyze the feasibility of a CBT blended intervention for AjD, as defined in the ICD-11, that combines a self-applied Internet intervention and videoconference sessions with a therapist.
Blended interventions are a growing field due to their many advantages. As mentioned above, it is difficult to access psychological treatments, not only for AjD, but for most mental disorders (Wang et al., 2005). Some authors have proposed that the incorporation of technologies into psychological treatments could improve their dissemination (Fairburn and Patel, 2017; Kazdin, 2017). One example is Internet-based treatments.
However, the lack of adherence to these interventions has led to the emergence of other alternatives, such as the blended format tested in this study. Previous studies conducted with other mental disorders have shown that blended interventions can be a viable, well-accepted and an effective alternative for many patients (Erbe et al., 2017; Schuster et al., 2018). In addition, this format can also make treatment more cost-effective reducing intervention costs (Erbe et al., 2017). However, in the case of AjD, as far as we know, only one study has tested a blended intervention (Leterme et al., 2020). Furthermore, it should be noted that, in this particular study, the face-to-face part was conducted by a nurse rather than a therapist. In addition, the computer-based component was performed in the same office, and not in an online format. Despite these differences, this study showed that an intervention using this format could also be effective in reducing the symptomatology of participants with AjD.
The intervention presented in this study protocol is based on evidence-based CBT components for AjD, and it includes different components of positive psychology and exercises adapted from Neiyemer's (2000) reconstruction of meaning approach to grief therapy. This treatment has already been tested in both face-to-face (Quero et al., 2019b) and self-applied formats (Rachyla et al., 2020), showing promising results.
To the best of our knowledge, this study presents the first blended intervention for AjD that combines a self-applied intervention via a web platform with videoconference sessions with a clinician every 10–12 days. In addition, it will be the first blended intervention for AjD in the Spanish language, which could bring this psychological treatment closer to all Spanish speakers.
We expect to show the feasibility of this blended intervention, in order to conduct a future RCT to determine the efficacy of an intervention with these characteristics for the treatment of adults with AjD.
4.1. Limitations
The main limitation of this study refers to the lack of randomization of participants. In this line, studies with a control group would be advisable in order to improve the design and methodology of a future RCT. Other limitations that may arise during the trial could have to do with difficulties in recruiting the sample, failures in the computer systems, or a high dropout rate. First, it is suggested that social media, posters and traditional media may not be sufficient to reach the estimated sample size. If it is necessary to increase the number of participants, we will also recruit by advertising in different universities or patient associations. Problems with computer systems will be taken care of by an engineer from the research team. Finally, regarding the dropout rate, we have adopted a strict criterion and contemplated a 17 % dropout rate in the sample size calculation.
5. Conclusion
The results of this study will provide valuable data about the feasibility and acceptability of a blended intervention for AjD. In addition, participants' use of the intervention and their feedback, expectations, and preferences will allow us to better understand their needs and adjust the design of future studies that test interventions for this disorder.
Consent for publication
Not applicable.
Funding
This study was supported by 2021 Research Promotion Plan at Universitat Jaume I (UJI-B2021-47), the Grant Prometeo Program for Research Groups of Excellence (CIPROM/2021/041 – Project “IMPULSA”) of the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital of the Valencian Community, a PhD grant of the Spanish Ministerio de Universidades (FPU20/00514) and CIBEROBN, an initiative of the ISCIIII (CB06 03/0052).
CRediT authorship contribution statement
SFB wrote the manuscript on the study protocol. SQ, SFB, JG, MP, and ADG collaborated in the study design. PC and SQ supervised and reviewed the writing of the article. All the authors read and approved the final manuscript.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
None.
Contributor Information
Sara Fernández-Buendía, Email: buendia@uji.es.
Pim Cuijpers, Email: p.cuijpers@vu.nl.
Jorge Grimaldos, Email: grimaldo@uji.es.
Amanda Díaz-García, Email: amandadiaz@unizar.es.
María Palau-Batet, Email: maria.palau@uji.es.
Soledad Quero, Email: squero@uji.es.
Data availability
Because this study is still in the recruitment phase, data cannot yet be shared.
References
- American Psychiatric Association [APA] 5th ed. American Psychiatric Association; Washington, DC: 2013. Diagnostic and Statistical Manual of Mental Disorders. [Google Scholar]
- Bachem R., Casey P. Adjustment disorder: a diagnosis whose time has come. J. Affect. Disord. 2018;227:243–253. doi: 10.1016/j.jad.2017.10.034. [DOI] [PubMed] [Google Scholar]
- Bachem R., Maercker A. Self-help interventions for adjustment disorder problems: a randomized waiting-list controlled study in a sample of burglary victims. Cogn. Behav. Ther. 2016;45(5):397–413. doi: 10.1080/16506073.2016.1191083. [DOI] [PubMed] [Google Scholar]
- Bangor A., Kortum P.T., Miller J.T. An empirical evaluation of the system usability scale. Intl. Journal of Human–Computer Interaction. 2008;24(6):574–594. doi: 10.1080/10447310802205776. [DOI] [Google Scholar]
- Bentley K.H., Gallagher M.W., Carl J.R., Barlow D.H. Development and validation of the overall depression severity and impairment scale. Psychol. Assess. 2014;26(3):815. doi: 10.1037/a0036247. [DOI] [PubMed] [Google Scholar]
- Bordin E.S. The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy. Theory, Research & Practice. 1979;16(3):252. doi: 10.1037/h0085885. [DOI] [Google Scholar]
- Borkovec T.D., Nau S.D. Credibility of analogue therapy rationales. J. Behav. Ther. Exp. Psychiatry. 1972;3(4):257–260. doi: 10.1016/0005-7916(72)90045-6. [DOI] [Google Scholar]
- Botella C., Baños R.M., Guillén V. In: Psicología Positiva Aplicada. Vázquez C., Hervás G., editors. DDB; Bilbao: 2008. Creciendo en la adversidad. Una propuesta de tratamiento para los trastornos adaptativos. [Google Scholar]
- Brooke, J. (1996). SUS-a quick and dirty usability scale. Usability Evaluation in Industry, 189(194), 4–7. Retrieved from: https://www.researchgate.net/publication/319394819_SUS_--_a_quick_and_dirty_usability_scale.
- Brown T.A., Di Nardo P.A., Barlow D.H. State University of New York at Albany; Phobia and Anxiety Disorders Clinic, Center for Stress and Anxiety Disorders: 1988. Anxiety Disorders Interview Schedule-Revised (ADIS-R) [Google Scholar]
- Castilla D., Jaén I., Suso-Ribera C., García-Soriano G., Zaragoza I., Breton-López J., Mira A., Díaz-García A., García-Palacios A. Psychometric properties of the Spanish full and short forms of the system usability scale (SUS): detecting the effect of negatively worded items. International Journal of Human–Computer Interaction. 2023;1-7 doi: 10.1080/10447318.2023.2209840. [DOI] [Google Scholar]
- Chan A.W., Tetzlaff J.M., Gøtzsche P.C., Altman D.G., Mann H., Berlin J.A., Dickersin K., Hróbjartsson A., Schulz K., Parulekar W.R., Krleža-Jerić K., Laupacis A., Moher D. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013;346 doi: 10.1136/bmj.e7586. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chan A.W., Tetzlaff J.M., Altman D.G., Laupacis A., Gøtzsche P.C., Krleža-Jerić K., Hróbjartsson A., Mann H., Dickersin K., Berlin J.A., Doré C.J., Parulekar W.R., Summerskill W.S.M., Groves T., Schulz K., Sox H.C., Rockhold F.W., Rennie D., Moher D. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann. Intern. Med. 2013;158(3):200–207. doi: 10.7326/0003-4819-158-3-201302050-00583. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cohen J. 2nd ed. Lawrence Earlbaum Associates; Hillsdale, NJ: 1988. Statistical Power Analysis for the Behavioral Sciences. [Google Scholar]
- Constantin D., Dinu E.A., Rogozea L., Burtea V., Leasu F.G. Therapeutic interventions for adjustment disorder: a systematic review. Am. J. Ther. 2020;27(4):e375–e386. doi: 10.1097/MJT.0000000000001170. [DOI] [PubMed] [Google Scholar]
- Crumbaugh J.C., Maholick L.T. An experimental study in existentialism: the psychometric approach to Frankl’s concept of noogenic neurosis. J. Clin. Psychol. 1964;20(2):200–207. doi: 10.1002/1097-4679(196404)20:2<200::AID-JCLP2270200203>3.0.CO;2-U. [DOI] [PubMed] [Google Scholar]
- Díaz-García A., González-Robles A., Mor S., Mira A., Quero S., García-Palacios A., Baños R.M., Botella C. Positive and Negative Affect Schedule (PANAS): psychometric properties of the online Spanish version in a clinical sample with emotional disorders. BMC Psychiatry. 2020;20:1–13. doi: 10.1186/s12888-020-2472-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Díaz-García A., González-Robles A., García-Palacios A., Fernández-Felipe I., Tur C., Castilla D., Botella C. Blended transdiagnostic group CBT for emotional disorders: a feasibility trial protocol. Internet Interv. 2021;23 doi: 10.1016/j.invent.2021.100363. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Domhardt M., Baumeister H. Psychotherapy of adjustment disorders: current state and future directions. World J. Biol. Psychiatry. 2018;19(sup1):S21–S35. doi: 10.1080/15622975.2018.1467041. [DOI] [PubMed] [Google Scholar]
- Eimontas J., Rimsaite Z., Gegieckaite G., Zelviene P., Kazlauskas E. Internet-based self-help intervention for ICD-11 adjustment disorder: preliminary findings. Psychiatry Q. 2018;89:451–460. doi: 10.1007/s11126-017-9547-2. [DOI] [PubMed] [Google Scholar]
- Eimontas J., Gegieckaite G., Dovydaitiene M., Mazulyte E., Rimsaite Z., Skruibis P., Zelviene P., Kazlauskas E. The role of therapist support on effectiveness of an internet-based modular self-help intervention for adjustment disorder: a randomized controlled trial. Anxiety Stress Coping. 2018;31(2):146–158. doi: 10.1080/10615806.2017.1385065. [DOI] [PubMed] [Google Scholar]
- Einsle F., Köllner V., Dannemann S., Maercker A. Development and validation of a self-report for the assessment of adjustment disorders. Psychol. Health Med. 2010;15(5):584–595. doi: 10.1080/13548506.2010.487107. [DOI] [PubMed] [Google Scholar]
- Eldridge S.M., Chan C.L., Campbell M.J., Bond C.M., Hopewell S., Thabane L., Lancaster G.A. CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ. 2016;355 doi: 10.1136/bmj.i5239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Erbe D., Eichert H.C., Riper H., Ebert D.D. Blending face-to-face and internet-based interventions for the treatment of mental disorders in adults: systematic review. J. Med. Internet Res. 2017;19(9) doi: 10.2196/jmir.6588. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Eysenbach G. CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J. Med. Internet Res. 2011;13(4) doi: 10.2196/jmir.1923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fairburn C.G., Patel V. The impact of digital technology on psychological treatments and their dissemination. Behav. Res. Ther. 2017;88:19–25. doi: 10.1016/j.brat.2016.08.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fernández-Álvarez J., Díaz-García A., González-Robles A., Baños R., García-Palacios A., Botella C. Dropping out of a transdiagnostic online intervention: a qualitative analysis of client’s experiences. Internet Interv. 2017;10:29–38. doi: 10.1016/j.invent.2017.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- First M.B., Spitzer R.L., Gibbon M., JBW, W. American Psychiatric Press; Washington, D.C.: 1996. Structured Clinical Interview for DSM-IV Axis I Disorders, Clinician Version (SCID-CV) [Google Scholar]
- Frisch M.B., Cornell J., Villanueva M., Retzlaff P.J. Clinical validation of the Quality of Life Inventory. A measure of life satisfaction for use in treatment planning and outcome assessment. Psychol. Assess. 1992;4(1):92. doi: 10.1037/1040-3590.4.1.92. [DOI] [Google Scholar]
- García-Alandete J., Martínez E.R., Sellés-Nohales P. Estructura factorial y consistencia interna de una versión española del Purpose-ln-Life Test. Universitas Psychologica. 2013;12(2):517–530. doi: 10.11144/Javeriana.UPSY12-2.efci. [DOI] [Google Scholar]
- Gómez-Penedo J.M., Berger T., Grosse-Holtforth M., Krieger T., Schröder J., Hohagen F., Meyer B., Moritz S., Klein J.P. The working alliance inventory for guided internet interventions (WAI-I) J. Clin. Psychol. 2020;76(6):973–986. doi: 10.1002/jclp.22823. [DOI] [PubMed] [Google Scholar]
- González-Robles A., Mira A., Miguel C., Molinari G., Díaz-García A., García-Palacios A., Bretón-López J.M., Quero S., Baños R.M., Botella C. A brief online transdiagnostic measure: psychometric properties of the Overall Anxiety Severity and Impairment Scale (OASIS) among Spanish patients with emotional disorders. PLoS One. 2018;13(11) doi: 10.1371/journal.pone.0206516. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hedman-Lagerlöf E., Carlbring P., Svärdman F., Riper H., Cuijpers P., Andersson G. Therapist-supported Internet-based cognitive behaviour therapy yields similar effects as face-to-face therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. World Psychiatry. 2023;22(2):305–314. doi: 10.1002/wps.21088. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kazdin A.E. Addressing the treatment gap: a key challenge for extending evidence-based psychosocial interventions. Behav. Res. Ther. 2017;88:7–18. doi: 10.1016/j.brat.2016.06.004. [DOI] [PubMed] [Google Scholar]
- Leterme A.C., Behal H., Demarty A.L., Barasino O., Rougegrez L., Labreuche J., Duhamel A., Vaiva G., Servant D. A blended cognitive behavioral intervention for patients with adjustment disorder with anxiety: a randomized controlled trial. Internet Interv. 2020;21 doi: 10.1016/j.invent.2020.100329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lorenz L., Bachem R.C., Maercker A. The adjustment disorder–new module 20 as a screening instrument: cluster analysis and cut-off values. The International Journal of Occupational and Environmental Medicine. 2016;7(4):215. doi: 10.15171/ijoem.2016.775. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mezzich J.E., Ruipérez M.A., Pérez C., Yoon G., Liu J., Mahmud S. The Spanish version of the quality of life index: presentation and validation. J. Nerv. Ment. Dis. 2000;188(5):301–305. doi: 10.1097/00005053-200005000-00008. [DOI] [PubMed] [Google Scholar]
- Mira A., González-Robles A., Molinari G., Miguel C., Díaz-García A., Bretón-López J., García-Palacios A., Quero S., Baños R.M., Botella C. Capturing the severity and impairment associated with depression: the overall depression severity and impairment scale (ODSIS) validation in a Spanish clinical sample. Front. Psychol. 2019;10:180. doi: 10.3389/fpsyt.2019.00180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Moser C., Bachem R., Berger T., Maercker A. ZIEL: Internet-based self-help for adjustment problems: results of a randomized controlled trial. J. Clin. Med. 2019;8(10):1655. doi: 10.3390/jcm8101655. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Neimeyer R.A. Searching for the meaning of meaning: grief therapy and the process of reconstruction. Death Stud. 2000;24(6):541–558. doi: 10.1080/07481180050121480. [DOI] [PubMed] [Google Scholar]
- Norman S.B., Hami Cissell S., Means-Christensen A.J., Stein M.B. Development and validation of an overall anxiety severity and impairment scale (OASIS) Depress. Anxiety. 2006;23(4):245–249. doi: 10.1002/da.20182. [DOI] [PubMed] [Google Scholar]
- O’Donnell M.L., Metcalf O., Watson L., Phelps A., Varker T. A systematic review of psychological and pharmacological treatments for adjustment disorder in adults. J. Trauma. Stress. 2018;31(3):321–331. doi: 10.1002/jts.22295. [DOI] [PubMed] [Google Scholar]
- O’Donnell M.L., Agathos J.A., Metcalf O., Gibson K., Lau W. Adjustment disorder: current developments and future directions. Int. J. Environ. Res. Public Health. 2019;16(14):2537. doi: 10.3390/ijerph16142537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Quero S., Mor S., Molés Amposta M., Rachyla I., Baños R., Botella C. Exploring the assessment of adjustment disorders: differences between a general and a clinical sample. Psychothema. 2019;31(1):17–23. doi: 10.7334/psicothema2018.159. [DOI] [PubMed] [Google Scholar]
- Quero S., Rachyla I., Molés M., Mor S., Tur C., Cuijpers P., López-Montoyo A., Botella C. Can between-session homework be delivered digitally? A pilot randomized clinical trial of CBT for adjustment disorders. Int. J. Environ. Res. Public Health. 2019;16(20):3842. doi: 10.3390/ijerph16203842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rachyla I., Mor S., Cuijpers P., Botella C., Castilla D., Quero S. A guided Internet-delivered intervention for adjustment disorders: a randomized controlled trial. Clin. Psychol. Psychother. 2020;28(2):313–324. doi: 10.1002/cpp.2483. [DOI] [PubMed] [Google Scholar]
- Rasing S.P., Stikkelbroek Y.A., Bodden D.H. Is digital treatment the Holy Grail? Literature review on computerized and blended treatment for depressive disorders in youth. Int. J. Environ. Res. Public Health. 2020;17(1):153. doi: 10.3390/ijerph17010153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schuster R., Sigl S., Berger T., Laireiter A.R. Patients’ experiences of blended group therapy for depression: fit and implications for the group setting. JMIR Mental Health. 2018;5(3) doi: 10.2196/mental.9613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Schuster R., Fischer E., Jansen C., Napravnik N., Rockinger S., Steger N., Laireiter A.R. Blending Internet-based and tele group treatment: acceptability, effects, and mechanisms of change of cognitive behavioral treatment for depression. Internet Interv. 2022;29 doi: 10.1016/j.invent.2022.100551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Svärdman F., Sjöwall D., Lindsäter E. Internet-delivered cognitive behavioral interventions to reduce elevated stress: a systematic review and meta-analysis. Internet Interv. 2022;29 doi: 10.1016/j.invent.2022.100553. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tedeschi R.G., Calhoun L.G. The posttraumatic growth inventory: measuring the positive legacy of trauma. J. Trauma. Stress. 1996;9:455–471. doi: 10.1007/BF02103658. [DOI] [PubMed] [Google Scholar]
- Wang P.S., Lane M., Olfson M., Pincus H.A., Wells K.B., Kessler R.C. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch. Gen. Psychiatry. 2005;62(6):629–640. doi: 10.1001/archpsyc.62.6.629. [DOI] [PubMed] [Google Scholar]
- Watson D., Clark L.A., Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 1988;54(6):1063. doi: 10.1037/0022-3514.54.6.1063. [DOI] [PubMed] [Google Scholar]
- Weiss T., Berger R. Reliability and validity of a Spanish version of the Posttraumatic Growth Inventory. Res. Soc. Work. Pract. 2006;16(2):191–199. doi: 10.1177/1049731505281374. [DOI] [Google Scholar]
- World Health Organization [WHO] 11th ed. WHO; Geneva: 2018. International Classification of Diseases. [Google Scholar]
- Zelviene P., Kazlauskas E. Adjustment disorder: current perspectives. Neuropsychiatr. Dis. Treat. 2018;375-381 doi: 10.2147/NDT.S121072. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Because this study is still in the recruitment phase, data cannot yet be shared.