https://orcid.org/0000-0001-5497-2743
Correction
14 Apr 2023: Cuijpers P, Heim E, Ramia JA, Burchert S, Carswell K, et al. (2023) Correction: Effects of a WHO-guided digital health intervention for depression in Syrian refugees in Lebanon: A randomized controlled trial. PLOS Medicine 20(4): e1004231. https://doi.org/10.1371/journal.pmed.1004231 View correction
Figures
Abstract
Background
Most displaced people with mental disorders in low- and middle-income countries do not receive effective care, and their access to care has deteriorated during the Coronavirus Disease 2019 (COVID-19) pandemic. Digital mental health interventions are scalable when digital access is adequate, and they can be safely delivered during the COVID-19 pandemic. We examined whether a new WHO-guided digital mental health intervention, Step-by-Step, in which participants were supported by a nonspecialist helper, was effective in reducing depression among displaced people in Lebanon.
Methods and findings
We conducted a single-blind, 2-arm pragmatic randomized clinical trial, comparing guided Step-by-Step with enhanced care as usual (ECAU) among displaced Syrians suffering from depression and impaired functioning in Lebanon. Primary outcomes were depression (Patient Health Questionnaire, PHQ-9) and impaired functioning (WHO Disability Assessment Schedule-12, WHODAS) at posttreatment. Secondary outcomes included subjective well-being, anxiety, post-traumatic stress, and self-described problems. A total of 569 displaced people from Syria with depression (PHQ-9 ≥ 10) and impaired functioning (WHODAS > 16) were randomized to Step-by-Step (N = 283; lost to follow-up: N = 167) or ECAU (N = 286; lost to follow-up: 133). Participants were considered to be lost to follow-up when they did not fill in the outcome measures at posttest or follow-up. Recruitment started on December 9, 2019 and was completed on July 9, 2020. The last follow-up assessments were collected in December 2020. The study team had access to the online platform, where they could see treatment arm assignment for each participant. All questionnaires were completed by participants online. Intention-to-treat (ITT) analyses showed intervention effects on depression (standardized mean differences [SMDs]: 0.48; 95% CI: 0.26; 0.70; p < 0.001), impaired functioning (SMD: 0.35; 95% CI: 0.14; 0.56; p < 0.001), post-traumatic stress (SMD: 0.36; 95% CI: 0.16; 0.56; p < 0.001), anxiety (SMD: 0.46; 95% CI: 0.24; 0.68; p < 0.001), subjective well-being (SMD: 0.47; 95% CI: 0.26; 0.68; p < 0.001), and self-identified personal problems (SMD: 0.49; 95% CI 0.28; 0.70; p < 0.001). Significant effects on all outcomes were maintained at 3 months follow-up. During the trial, one serious adverse event occurred, unrelated to the intervention. The main limitation of the current trial is the high dropout rate.
Author summary
Why was this study done?
- Depression is a major public health problem, and depression rates in people who are forcibly displaced are even higher.
- Effective treatment of depression is hardly available for displaced people.
- Digital mental health interventions may be a scalable solution for displaced people suffering from depression.
What did the researchers do and find?
- We tested a digital tool for reducing depression in displaced people from Syria who live in Lebanon, based on an intervention for depression that was developed by WHO.
- We randomly assigned 569 displaced people to the digital tool or to a control group who only received usual care and found that people who received the digital tool were much less depressed after the intervention than the people who only received usual care. We also found important and statistically significant effects on anxiety, impaired functioning, post-traumatic stress, and well-being.
- Most effects persisted at 3 months after the intervention.
What do these findings mean?
- We found that a guided, digital intervention was effective in reducing depression in displaced people in Lebanon.
- The intervention we examined can be an important tool to reduce depression in displaced people that have digital access.
- The findings should be interpreted with caution because of the large number of participants who dropped out of the study.
Citation: Cuijpers P, Heim E, Abi Ramia J, Burchert S, Carswell K, Cornelisz I, et al. (2022) Effects of a WHO-guided digital health intervention for depression in Syrian refugees in Lebanon: A randomized controlled trial. PLoS Med 19(6): e1004025. https://doi.org/10.1371/journal.pmed.1004025
Academic Editor: Kolitha Wickramage, International Organization for Migration, SRI LANKA
Received: October 11, 2021; Accepted: May 19, 2022; Published: June 23, 2022
Copyright: © 2022 Cuijpers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The anonymised data are available at the DANS data repository (https://dans.knaw.nl/en/) at the following url: https://doi.org/10.17026/dans-zey-hjpk and can be acquired through the data management committee of the Faculty of Behavioural and Movement Sciences of the Vrije Universiteit Amsterdam at: data.committee.fgb@vu.nl.
Funding: This study was funded by the Research for Health in Humanitarian Crises (R2HC, managed by Elrha; https://www.elrha.org) (resources mobilized by MvO). The study used an open source research infrastructure developed by Freie Universität Berlin as part of STRENGTHS project (funded by the European Union's Horizon 2020 Research and Innovation Program Societal Challenges; agreement 733337; https://ec.europa.eu/programmes/horizon2020) (resources mobilized by CK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: CONSORT, Consolidated Standards of Reporting Trials; COVID-19, Coronavirus Disease 2019; CSQ, Client Satisfaction Questionnaire; ECAU, enhanced care as usual; ITT, intention-to-treat; NNT, numbers needed to treat; OR, odds ratio; PHQ-9, Patient Health Questionnaire; PSYCHLOPS, Psychological Outcomes Profile; RCT, randomised controlled trial; RLFB, Random Forest Lee bound; SMD, standardized mean difference; WHODAS, WHO Disability Assessment Schedule-12
Introduction
In 2022, an estimated 82 million people were forcibly displaced due to war, conflict, or persecution, including 21 million refugees [1]. The greatest contemporary crisis related to displaced people has been caused by the war in Syria, involving almost 6 million refugees [2]. Lebanon, with a total population of close to 7 million, currently hosts about 1.5 million displaced Syrians. Concurrently, Lebanon faces multiple other emergencies, including a collapsing economy, severe political turmoil, an explosion of neglected ammonium nitrate destroying large parts of the capital Beirut, and the impact of the Coronavirus Disease 2019 (COVID-19) pandemic [3].
During war, people often face multiple threats to life, loss of family, sexual and physical abuse, and lack of shelter or nutrition [4,5]. After fleeing for safety, displaced people experience continuing difficulties, including unmet basic needs, language barriers, uncertainty about the future, social isolation, and discrimination [4,6]. As a result, they are at risk of mental disorders, such as depression, anxiety, and post-traumatic stress [7]. It has been estimated that 22% of displaced, war-affected Syrians in Lebanon suffer from moderate to severe depressive symptoms [8].
Although depression and other common mental disorders are a leading cause of disability [9], the vast majority of displaced people do not receive treatment. This is especially true in low- and middle-income countries where only 1 in 27 people with depression are likely to receive evidence-based treatment [10] and where less than 1 per 1,000 displaced people seeks help from health services for common mental disorders [11].
Lebanon currently seeks to strengthen its mental health services. The National Mental Health Programme aims to scale up mental health care [12], but there have been limited resources, and there are recent challenges offering care safely during the pandemic and the political and economic crisis. One strategy to scale up services involves digital interventions, as research from high-income countries suggests that mobile apps can be effective [13]. Digital interventions can be either unguided or guided by a trained nonspecialist helper who supports participants in their use of self-help materials. While unguided interventions are less effective, guided self-help interventions are no less effective than face-to-face treatments [14]. Thus far, no studies on guided digital mental health interventions have been conducted in populations of displaced people in low- and middle-income countries.
A new WHO digital mental health intervention, “Step-by-Step,” based on behavioral activation to treat depression, can be delivered with guidance from nonspecialist helpers [15]. The current study examines the effects of guided “Step-by-Step,” compared to enhanced care as usual (ECAU) in displaced Syrians in Lebanon.
Methods
Design
This single-blind, 2-arm pragmatic randomized clinical trial examined the effects of a digital health intervention for depression compared with ECAU in displaced Syrians in Lebanon. The study was conducted together with an identical study in Lebanese citizens, which is reported elsewhere [16]. Ethical approval was received from the WHO Ethical Review Committee (ERC.0002797) and Saint-Joseph’s University, Beirut (CEHDF862). It was registered at ClinicalTrials.gov (NCT03720769). The trial protocol, an open pilot trial, and a feasibility randomised controlled trial (RCT) have been published [17–19].
This study is reported as per the Consolidated Standards of Reporting Trials (CONSORT) guideline (S1 Checklist).
Procedures
We included participants meeting the following criteria: (1) Syrian displaced people; (2) above 18 years of age; (3) residing in Lebanon; (4) who understood and spoke Arabic or English; (5) had access to an internet-connected device; (6) had moderate or severe depressive symptoms (Patient Health Questionnaire [PHQ-9] ≥ 10) [20]l and (7) experienced functional impairment (WHO Disability Assessment Schedule-12 (WHODAS > 16)) [21]. Participants at imminent risk of suicide (based on a question on serious thoughts or a plan to end one’s life in the past month) were excluded. They received an on-screen message explaining that they may need additional mental health support. A national suicide hotline (phone number) was installed by a local NGO in Lebanon, which provides 24-hour support and referral to specialized care. People who respond “yes” to the PHQ question on suicide were informed about this 24-hour service, along with a list of mhGAP Interventions Guide trained primary health care facilities and were encouraged to seek help.
Recruitment of participants took place through advertising for the research project on several social media platforms, by posting and boosting posts on the official social media pages of the National Mental Health Programme on Facebook and Instagram. Additionally, outreach methods took place with the network of NGOs and UN agencies taking part in a mental health and psychosocial support taskforce whereby meetings were held in different regions with the Syrian community to introduce the project, followed by WhatsApp broadcasts that were sent by the organizations to their Syrian beneficiaries.
Interested participants could access the web version or download the mobile app, where information was given about the intervention and the study, including an animated video explaining key points. After completing informed consent and the baseline self-screening instruments, participants who met inclusion criteria were asked to complete additional baseline questionnaires. Informed consent was obtained through the online platform. Participants had to agree to 8 statements (e.g., I declare that I have read and understood the study information) by clicking the corresponding tick boxes. Otherwise, they were not able to proceed to the completion of the baseline questionnaires and to the intervention. As remuneration for completing all the questionnaires, users received $20 phone credit. Recruitment started on December 9, 2019 and was completed on July 9, 2020. The last follow-up assessments were collected in December 2020.
Participants were randomized to the intervention or ECAU, using a permuted block randomization with 1:1 allocation ratio within blocks of random length between 2 and 8. The randomization was handled by an algorithm for permuted block randomization that was built into the app and not accessible to the research team. The algorithm generated a random sequence of blocks with varying length. In each block, the number of seats for both groups was even, and the order was fully random.
The study team (i.e., coordinator and e-helpers) had access to the online platform, where they could see treatment arm assignment for each participant. However, as all questionnaires were completed by participants online, the fact that the study team was not blinded to treatment arm assignment did not have any effect on participants’ responses.
Study arms
Intervention.
Step-by-Step is a 5-session intervention, designed to treat depression through an internet-connected device [15]. It provides psychoeducation and training in behavioral activation through an illustrated narrative, with additional therapeutic techniques such as stress management, a gratitude exercise, positive self-talk, strengthening social support, and relapse prevention.
Step-by-Step includes 5 story sessions that are illustrated and audio recorded. Each session is divided into 3 smaller parts, which take altogether 20 minutes on average to read. Every session unlocks after 4 days of completing the previous session. This is to give enough time for the participant to practice the skills and exercises that they learned in the previous session. Users are recommended to complete 1 session (with all its 3 parts) every week. The program is thus meant to be completed over a period of 5 weeks to 8 weeks, accounting for delays. More information is in a paper about the development of the intervention [15].
The narrative was adapted to the local context, considering gender, linguistic, and cultural nuances among displaced Syrians [22]. It has a female and male version, each with 2 versions, 1 for married people with children and 1 for unmarried people. Participants can also choose the appearance of the character, broadly reflecting the main cultural groups in Lebanon (Lebanese, Syrians, and Palestinians). The intervention was provided as a hybrid app for iOS, Android, and web browsers using technical infrastructure developed by the Freie Universität Berlin [23]. Users who accessed the intervention received email or phone-based notifications, covering reminders of assessments due or upcoming, new sessions available, and gratitude for study participation. They could opt out of notifications any time.
Users of the intervention were supported by trained nonspecialists (“e-helpers”) who offered weekly phone or message-based contact with users to provide support (max. 15 minutes per week). E-helpers had a background in psychology or health, but had no previous experience in delivering mental health care. While the content of the intervention was delivered through the app, the e-helpers were trained to provide technical and emotional support to strengthen users’ motivation, to assess and refer participants at high risk of suicide, child abuse, or gender-based violence, and to support participants in acute distress, using preset protocols. E-helpers passed a competency test after the training to be involved in the trial. A treatment fidelity checklist was used, and 5% of the guidance calls and messages were rated. Training was delivered over 5 days with ongoing weekly group supervision—and, on demand, individual meetings—being provided by one local clinical psychologist.
Participants were considered inactive if they did not use the app for more than 3 weeks and did not respond to the e-helper reminders for 3 consecutive weeks. They then received an email informing them that the helpers would stop contacting them. Those who proactively conveyed that they would like to stop were also considered dropped out. The relevant e-helper then asked them if they want their data to be removed from the study and shared an exit survey with them by email to inquire about reasons for quitting.
ECAU.
ECAU consisted of basic psychoeducation and referral to evidence-based care. Psychoeducation on depression and anxiety was delivered through the app or website. The text for the psychoeducational messages was taken from the first session of Step-by-Step to ensure identical information. After the psychoeducation, users received a list of primary health care facilities with nonspecialized staff trained in evidence-based mental health care [24].
Outcomes
Primary outcomes were depressive symptoms measured by the PHQ-9 [20] and functional impairment measured by the WHODAS-12 2.0 [21] at posttreatment. The PHQ-9 is a 9-item instrument measuring severity of depression, with a cutoff score of ≥10 indicating moderate or severe depression, which has also been validated in Lebanon [25]. The WHODAS was used to measure functional impairment, as it provides a generic assessment of health and disability across 6 domains (cognition, mobility, self-care, getting along, life activities, and participation).
Secondary outcomes included subjective well-being, anxiety, and post-traumatic stress assessed by the 5-item WHO-5 Wellbeing Index [26]; the 7-item GAD-7 [27]; and the 8-item PTSD Checklist for DSM-5; PCL-5) [28], respectively. The Psychological Outcomes Profile (PSYCHLOPS) instrument was used to identify and rate self-described problems [29]. Satisfaction with the intervention was measured with the Client Satisfaction Questionnaire (CSQ-3), a measure of client satisfaction with mental health services [30]. A more extensive description of the measures can be found in the protocol paper [17].
Outcomes were measured at baseline, posttreatment (8 weeks after baseline), and follow-up (3 months posttreatment).
Analyses
The RCT was designed to have >90% power with α = .05 to detect a 0.5 standardized mean difference (SMD) between the intervention and control group. Assuming 70% dropout [31,32], we planned to recruit 568 participants to show that the intervention was effective. We compared the intervention and control group on demographic and clinical characteristics with χ2 and variance analyses. The main outcomes were examined with intention-to-treat (ITT) analysis. Per-protocol analyses were secondary analyses.
For ITT analyses, regression models were estimated with treatment assignment status as principal predictor. To address potential bias concerns due to selective attrition, missing outcome observations were calculated using multiple imputation exploiting prescores and prespecified background characteristics (gender, age, education, and symptom severity). Given we consider continuous outcomes, multivariate normal regression imputation with an iterative Markov chain Monte Carlo method was used based on initial treatment assignment. The number of imputations required was determined using the 2-stage approach that ensures the replicability of SE estimates [33]. Performing this procedure indicated that at least 82 imputations were required, after which we decided on 150 imputations.
The prespecified covariates and baseline measurement of primary endpoint were added to the baseline model for improved precision. Effect sizes calculated are Hedges’ g by combining the multiple imputation estimation results using Rubin’s rules.
To examine the robustness of the results to differential nonrandom attrition across treatment arms, Random Forest Lee bounds (RFLBs) were estimated [34,35]. This bounding approach applies extreme worst- and best-case assumptions about the impact of differential selective attrition on the estimated effect for never-attriters. More details of these analyses are given in S1 Appendix.
To guide clinical interpretation, we calculated the proportion of participants who responded (>50% reduction of PHQ-9 symptoms) and completely remitted (<5 on the PHQ-9).
Concerns of multiple testing error were addressed by maintaining an experiment-wise type I error of 5%. To address potential heterogeneity, treatment effects were estimated for the 2 conditions (e.g., based on prescores). Finally, average treatment effects on the treated were estimated, and corresponding measures of clinically meaningful change and numbers needed to treat (NNT) were explored [36].
All analyses were conducted in STATA/SE 16.0 [37].
Results
Participants
Of 1,380 persons assessed for eligibility, 569 met inclusion criteria and were randomized (Fig 1). A total of 283 participants were randomized to the intervention and 286 to ECAU. The posttreatment assessment was returned by 53.8% and the 3 months follow-up assessment by 47.3% of respondents (i.e., 46.2% and 52.7% dropout, respectively). The recruitment started on December 9, 2019 and ended on July 9, 2020. The original plan was to start recruitment in November 2019; however, due to the eruption of protests in Lebanon and political unrest in 2019, it was postponed for 1 month. The completion of data collection was also delayed for about 2 months. No other deviations from the protocol occurred.
The sociodemographic characteristics of the participants are summarized in Table 1. The average age was 31.5. The majority of the participants were female (58.3%), and the majority were married (70.1%). Most had primary (32.0%) or secondary education (36.7%), and the majority were unemployed (58.7%). There were no significant differences between intervention and control group. Due to the recruitment procedures, no baseline information was missing for participants.
Primary outcome
The ITT analyses showed significant treatment effects for both primary outcomes, depression (b = −2.81; SE = 0.66; p < 0.001), and functional impairment (b = −3.27; SE = 0.98; p = 0.001). Effect sizes were moderate for depression (g = 0.48; 95% CI: 0.26; 0.70) and functional impairment (g = 0.35; 95% CI: 0.14; 0.56) (Tables 2 and 3).
At 3 months follow-up, the intervention effect was maintained for depression (b = −3.63; SE = 0.72; p < 0.001) with a moderate to large effect size (g = 0.61; 95% CI: 0.37; 0.85), and a moderate effect size for functional impairment (b = −4.28; SE = 1.13, p < 0.001; g = 0.45; 95% CI: 0.22; 0.68). Estimating worst- and best-case scenarios for the potential impact of selective differential attrition yielded RFLBs for never-attriters (model 2 in Table 3) that are always in the same direction as the ITT results, but with worst-case bounds not statistically significant.
Secondary outcomes
According to ITT analyses, all secondary outcomes indicated significant results (all p-values < 0.002) with moderate SMDs: 0.47 for subjective well-being (WHO-5), 0.46 for anxiety (GAD-7), 0.36 for post-traumatic stress (PCL-5), and 0.49 for personal problems (PSYCHLOPS) (Tables 2 and 3). At 3 months follow-up, the intervention continued to be significantly more effective than ECAU for all outcomes (all p’s < 0.03; Table 3), with effect sizes that were comparable to those at posttest.
Response and complete remission
For the ITT sample, approximately 2 in 5 treated people showed a treatment response (37.1%), versus 1 in 7 (13.3%) in the control group (odds ratio [OR] = 3.8; 95% CI: 2.5; 5.8; p < 0.001). Moreover, approximately 1 in 5 (20.8%) treated people completely remitted versus 1 in 20 (4.9%) in the control group (OR = 5.1; 2.8; 9.4; p < 0.001). The NNT were 4 (95% CI: 3.3; 5.9) for response and 6 (95% CI: 4.7; 9.4) for complete remission for the ITT sample. The analysis of the sample of participants who experienced complete remission resulted in comparable outcomes to the ITT sample (Table 4).
Other outcomes
Of 283 participants in the intervention condition, 203 (71.7%) finished the introduction session, 119 (42.0%) finished at least 3 of 5 sessions, and 91 (32.2%) finished all sessions. Of the 131 participants who completed the postassessment, approximately half indicated that most or almost all of their needs were met (48.1%). A large majority responded that they were mostly or very much satisfied (89.3%) and that they would come back to the program if they were to seek help again (96.9%). Fidelity checks revealed 6% minor deviations from the treatment protocol, such as a helper not reviewing the story with a user or not reviewing practice exercises. During the trial, one serious adverse event occurred (a hospitalization in the intervention group, unrelated to the intervention).
A qualitative process evaluation was conducted and interviews were held with participants. Feedback on the content, delivery model of the intervention, and dropout was solicited and will be published in a separate paper.
Discussion
Summary of the main findings
This study supports the value of digital self-help, in a setting where displaced people were subjected to a range of co-occurring adversities. The fact that the study was able to rapidly complete recruitment during the COVID-19 pandemic shows the value of digital health at a time when physical distancing is required. We found that this new WHO digital mental health intervention, Step-by-Step, is effective in reducing mental health problems among displaced, war-affected Syrians living in Lebanon. Moderate effects on our primary outcome variables, depression and impaired functioning, were found at posttreatment and 3 months follow-up. The intervention also had significant effects on anxiety, post-traumatic stress, well-being, and personal problems, and these effects were maintained at follow-up. With NNTs of 4 (response) to 6 (complete remission) in the ITT sample, the clinical relevance of this intervention is considerable.
What this study adds
These results are consistent with previous findings showing that e-health in general [38], as well as mobile health apps [13], can effectively reduce mental health problems. However, most of the previous research has been conducted in high-income countries. This study shows that mobile interventions can also be effective in people with mental health problems in a lower-resourced country, among displaced people. The study was conducted in the setting where it should ultimately be implemented, and we think therefore that the results can be generalized well to routine care for displaced persons in Lebanon, as well as to other comparable displaced populations. This can be seen as a strong indication that low cost digital interventions, like Step-by-Step may be used to develop a basic infrastructure for mental health care for common mental disorders in these populations.
Strengths and limitations
Strengths of this study include the implementation in a country exposed to multiple crises, adaptation to the local context, the large sample size, automated randomization shielding against researcher bias, automated assessment ensuring blinded data collection, the overall strict design and analyses, and the central involvement of Lebanon’s National Mental Health Program, positioning it to scale up this intervention nationally.
Limitations include the high level of dropout, which is inherent to e-mental health interventions and research [39], and for which we had powered the study. Also, we did not conduct clinical diagnostic interviews. Furthermore, we only examined the effects at 3 months follow-up, though effects were maintained at least over that period. Finally, the intervention itself is limited, because it requires digital access, which is inequitably distributed in populations.
Implications and next steps
Although the results of this study are very encouraging, more research is needed to establish the long-term effects of the intervention. It would also be useful to examine in more depth what happens with those who dropped out of the intervention and what is needed to retain them in the intervention or develop an alternative treatment for them. Because this intervention was specifically aimed at depression, it would also be useful to examine the possibility to develop comparable interventions for other common mental disorders, such as post-traumatic stress disorder and anxiety disorders, especially in displaced populations.
We do think that the results of this study indicate that dissemination of this intervention is justified in Lebanon, as it was tested in exactly the same circumstances where it is to be disseminated. Testing and use in other comparable settings in low- and middle income countries, as well as in displaced populations, should also be considered.
Conclusions
Despite these limitations, we conclude that the digital intervention had a statistically significant and meaningful effect on depression, functional impairment, anxiety, post-traumatic stress, subjective well-being, and self-identified problems among displaced, war-affected Syrians living in Lebanon. To the best of our knowledge, this study is the first to show that a digital intervention supported by human helpers can contribute considerably to improving mental health among displaced people in a low-resourced setting. Informed by these results and those of a second trial, WHO will release Step-by-Step as an open-access intervention to fill the gap of publicly available evidence-based psychological interventions in global mental health [40]. Lebanon’s National Mental Health Program is now scaling up the intervention in the country.
Supporting information
S1 Checklist. CONSORT Checklist.
CONSORT, Consolidated Standards of Reporting Trials.
https://doi.org/10.1371/journal.pmed.1004025.s001
(DOC)
S1 Appendix. Details about the statistical procedures.
https://doi.org/10.1371/journal.pmed.1004025.s003
(DOCX)
Acknowledgments
Step-by-Step was developed by WHO in collaboration with the National Mental Health Programme of the Ministry of Public Health in Lebanon, Freie Universität Berlin, and University of Zurich.
We thank the following colleagues: Rasha Abi Hana, Ghida Anani, Ahmad Akar, Jean Boutros, Hajar Chamoun, Carole El Sayed, Gaelle Fahed, Nayla Geagea, Layal Hamze, Melissa Harper Shehadeh, Yara Hasbany, Maria Hayek, Maha Hodroj, Sally Khoury, Nour Kik, Helen Patuck, Perrine Posbic, Jerome Seregni, Jihane bou Sleiman, Sarah Watts, and Charbel Zgheib for their contributions.
The authors alone are responsible for the views expressed in this article, and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.
The CSQ is copyrighted intellectual property and used with permission of the copyright holder: www.csqscales.com.
References
- 1.
United Nations High Commissioner for Refugees. Figures at a Glance. Available from: https://www.unhcr.org/figures-at-a-glance.html.
- 2.
UNHCR (2021) Operational Portal: Refugee Situation. Available from: https://data2.unhcr.org/en/situations/syria.
- 3. Abouzeid MH. Lebanon’s humanitarian crisis escalates after the Beirut blast. Lancet. 2020;396:1380–2. pmid:32919521
- 4. Acarturk C, McGrath M, Roberts B, Ilkkursun Z, Cuijpers P, Sijbrandij M, et al. Prevalence and predictors of common mental disorders among Syrian refugees in Istanbul, Turkey: A cross-sectional study. Soc Psychiatry Psychiatr Epidemiol. 2021;56:475–84. pmid:32789561
- 5. Georgiadou E, Zbidat A, Schmitt GM, Erim Y. Prevalence of mental distress among Syrian refugees with residence permis- sion in Germany: a registry-based study. Front Psych. 2018;9:393.
- 6. Ben Farhat J, Blanchet K, Juul Bjertrup P, Veizis A, Perrin C, Coulborn RM, et al. Syrian refugees in Greece: experience with violence, mental health status, and access to information during the journey and while in Greece. BMC Med. 2018;16:40. pmid:29530041
- 7. Charlson F, van Ommeren M, Flaxman A, et al. New WHO prevalence estimates of mental disorders in conflict settings: a sys- tematic review and meta-analysis. Lancet. 2019;394:240–8. pmid:31200992
- 8. Naal H, Nabulsi D, El Arnaout N, Abdouni L, Dimassi H, Harb R, et al. Prevalence of depression symptoms and associated sociodemographic and clinical correlates among Syrian refugees in Lebanon. BMC Public Health. 2021;21:217. pmid:33499834
- 9.
Institute of health Metrics and Evaluation. Global Health Data Exchange (GHDx). Available from: http://ghdx.healthdata.org/gbd-results-tool?params=gbd-api-2019-permalink/42d9929f694a93a088663879c8c9cb77.
- 10. Thornicroft G, Chatterji S, Evans-Lacko S, Gruber M, Sampson N, Aguilar-Gaxiola S, et al. Undertreatment of people with major depressive disorder in 21 countries. Br J Psychiatry. 2017;210:119–24. pmid:27908899
- 11. Kane JC, Ventevogel P, Spiegel P, Bass JK, van Ommeren M, Tol WA. Mental, neurological, and substance use problems among refugees in primary health care: analysis of the Health Information System in 90 refugee camps. BMC Med. 2014;12:228. pmid:25420518
- 12.
Lebanese Ministry of Public Health. The Mental Health and Substance Use—Prevention, Promotion and Treatment- Situation Analysis and Strategy for Lebanon 2015–2020. Beirut: Lebanese Ministry of Public Health, 2014. Available from:http://www.moph.gov.lb/en/Pages/6/553/nmhp.
- 13. Linardon J, Cuijpers P, Carlbring P, Messer M, Fuller-Tyszkiewicz M. The efficacy of app-supported smartphone interventions for mental health problems: a meta-analysis of randomized controlled trials. World Psychiatry. 2019;18:325–36. pmid:31496095
- 14. Cuijpers P, Noma H, Karyotaki E, Cipriani A, Furukawa TA. Effectiveness and Acceptability of Cognitive Behavior Therapy Delivery Formats in Adults With Depression: A Network Meta-analysis. JAMA Psychiat. 2019;76:700–7. pmid:30994877
- 15. Carswell K, Harper-Shehadeh M, Watts S, Van’t Hof E, Abi Ramia J. Heim E, et al. Step-by-Step: a new WHO digital mental health intervention for depression. mHealth. 2018;4:34. pmid:30225240
- 16. Cuijpers P, Heim E, Abi Ramia J, Burchert S, Carswell K, Cornelisz I, et al. A Guided Digital Health Intervention for Depression in Lebanon: Randomized Trial. Evid Based Ment Health. pmid:35577536
- 17. van’t Hof E, Heim E, Abi Ramia J, Burchert S, Cornelisz I, Cuijpers P, et al. Evaluating the Effectiveness of an E-Mental Health Intervention for People Living in Lebanon: Protocol for Two Randomized Controlled Trials. JMIR Res Protoc. 2021;10:e21585. pmid:33507158
- 18. Harper Shehadeh MJ, Abi Ramia J, Cuijpers P, El Chammay R, Heim E, et al. Step-by-Step, an E-Mental Health Intervention for Depression: A Mixed Methods Pilot Study From Lebanon. Front Psych. 2020;10:986. pmid:32116815
- 19. Heim E, Ramia JA, Hana RA, Burchert S, Carswell K, Cornelisz I, et al. Step-by-step: Feasibility randomised controlled trial of a mobile-based intervention for depression among populations affected by adversity in Lebanon. Internet Interv. 2021;24(3):100380. pmid:33747798
- 20. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606–13. pmid:11556941
- 21.
Ustun T, Kostanjesek N, Chatterji S, Rehm J, Organization. WH. Measuring health and disability: manual for WHO Disability Assessment Schedule (WHODAS 2.0). Geneva: WHO; 2010.
- 22. Abi Ramia J, Harper Shehadeh M, Kheir W, Zoghbi E, Watts S, Heim E, et al. Community cognitive interviewing to inform local adaptations of an e-mental health intervention in Lebanon. Glob Ment Health. 2018;5:e39. pmid:30637112
- 23. Burchert S, Alkneme MS, Bird M, Carswell K, Cuijpers P, Hansen P, et al. User-Centered App Adaptation of a Low-Intensity E-Mental Health Intervention for Syrian Refugees. Front Psych. 2018;9:663. pmid:30740065
- 24.
WHO. mhGAP Intervention Guide—Version 2.0 for mental, neurological and substance use disorders in non-specialized health settings. Geneva: WHO; 2016.
- 25. Sawaya H, Atoui M, Hamadeh A, Zeinoun P, Nahas Z. Adaptation and initial validation of the Patient Health Questionnaire—9 (PHQ-9) and the Generalized Anxiety Disorder—7 Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample. Psychiatry Res. 2016;239:245–52. pmid:27031595
- 26. Bech P, Olsen LR, Kjoller M, Rasmussen NK. Measuring well-being rather than the absence of distress symptoms: a comparison of the SF-36 Mental Health subscale and the WHO-Five Well-Being Scale. Int J Meth Psychiatric Res. 2003;12:85–91.
- 27. Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–7. pmid:16717171
- 28. van Price M, Price M, Szafranski DD. Investigation of abbreviated 4 and 8 item versions of the PTSD Checklist 5. Psychiatry Res. 2016;239:124–30. pmid:27137973
- 29. Ashworth M, Shepherd M, Christey J, Matthews V, Wright K, Parmentier H, et al. A client-generated psychometric instrument: The development of ‘PSYCHLOPS’ (‘Psychological Outcome Profiles’). Counsel Psychother Res. 2004;4:27–33.
- 30. Larsen DL, Attkisson CC, Hargreaves WA, Nguyen TD. Assessment of client/patient satisfaction: development of a general scale. Eval Program Plann. 1979;2:197–207. pmid:10245370
- 31. Josephine K, Josefine L, Philipp D, David E, Harald B. Internet- and mobile-based depression interventions for people with diagnosed depression: A systematic review and meta-analysis. J Affect Disord. 2017;223:28–40. pmid:28715726
- 32. Cuijpers P, Karyotaki E, Reijnders M, Purgato M, Barbui C. Psychotherapies for depression in low- and middle-income countries: a meta-analysis. World Psychiatry. 2018;17:90–101. pmid:29352530
- 33. Hippel V, Paul T. How many imputations do you need? A two-stage calculation using a quadratic rule. Sociol Meth Res. 2020;49:699–718.
- 34. Lee DS. Training, wages, and sample selection: Estimating sharp bounds on treatment effects. Rev Econ Stud. 2009;76:1071–102.
- 35. Cornelisz I, Cuijpers P, Donker T, van Klaveren C. Addressing missing data in randomized clinical trials: A causal inference perspective. PLoS ONE. 2020;15:e0234349. pmid:32628678
- 36. Laupacis A, Sackett DL, Roberts RS. An assessment of clinically useful measures of the consequences of treatment. Nw Engl J Med. 1988;318:1728–33. pmid:3374545
- 37.
StataCorp. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC, 2019.
- 38. Andrews G, Basu A, Cuijpers P, Craske MG, McEvoy P, English CL, et al. Computer therapy for the anxiety and depression disorders is effective, acceptable and practical health care: An updated meta-analysis. J Anxiety Disord. 2018;55:70–8. pmid:29422409
- 39. van Ballegooijen W, Cuijpers P, van Straten A, Karyotaki E, Andersson G, Smit JH, et al. Adherence to Internet-based and face-to-face cognitive behavioural therapy for depression: a meta-analysis. PLoS ONE. 2014;9:e100674. pmid:25029507
- 40. Watts S, van Ommeren M, Cuijpers P. Open access of psychological intervention manuals. World Psychiatry. 2020;19:251–2. pmid:32394577