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German Version of the Mobile Agnew Relationship Measure: Translation and Validation Study
Abstract
Background
The mobile Agnew Relationship Measure (mARM) is a self-report questionnaire for the evaluation of digital mental health interventions and their interactions with users. With the global increase in digital mental health intervention research, translated measures are required to conduct research with local populations.
Objective
The aim of this study was to translate and validate the original English version of the mARM into a German version (mARM-G).
Methods
A total of 2 native German speakers who spoke English as their second language conducted forward translation of the original items. This version was then back translated by 2 native German speakers with a fluent knowledge of English. An independent bilingual reviewer then compared these drafts and created a final German version. The mARM-G was validated by 15 experts in the field of mobile app development and 15 nonexperts for content validity and face validity; 144 participants were recruited to conduct reliability testing as well as confirmatory factor analysis.
Results
The content validity index of the mARM-G was 0.90 (expert ratings) and 0.79 (nonexperts). The face validity index was 0.89 (experts) and 0.86 (nonexperts). Internal consistency for the entire scale was Cronbach α=.91. Confirmatory factor analysis results were as follows: the chi-square statistic to df ratio was 1.66. Comparative Fit Index was 0.87 and the Tucker-Lewis Index was 0.86. The root mean square error of approximation was 0.07.
Conclusions
The mARM-G is a valid and reliable tool that can be used for future studies in German-speaking countries.
Fully automated mental health smartphone apps show strong promise in increasing access to psychological support. Therefore, it is crucial to understand how to make these apps effective. The therapeutic alliance (TA), or the relationship between healthcare professionals and clients, is considered fundamental to successful treatment outcomes in face-to-face therapy. Thus, understanding the TA in the context of fully automated apps would bring us insights into building effective smartphone apps which engage users. However, the concept of a digital therapeutic alliance (DTA) in the context of fully automated mental health smartphone apps is nascent and under-researched, and only a handful of studies have been published in this area. In particular, no published review paper examined the DTA in the context of fully automated apps. The objective of this review was to integrate the extant literature to identify research gaps and future directions in the investigation of DTA in relation to fully automated mental health smartphone apps. Our findings suggest that the DTA in relation to fully automated smartphone apps needs to be conceptualized differently to traditional face-to-face TA. First, the role of bond in the context of fully automated apps is unclear. Second, human components of face-to-face TA, such as empathy, are hard to achieve in the digital context. Third, some users may perceive apps as more non-judgmental and flexible, which may further influence DTA formation. Subdisciplines of computer science, such as affective computing and positive computing, and some human-computer interaction (HCI) theories, such as those of persuasive technology and human-app attachment, can potentially help to foster a sense of empathy, build tasks and goals and develop bond or an attachment between users and apps, which may further contribute to DTA formation in fully automated smartphone apps. Whilst the review produced a relatively limited quantity of literature, this reflects the novelty of the topic and the need for further research.
Introduction: Developing a good therapeutic alliance is considered essential for the responsible delivery of psychotherapy. Text-based digital psychotherapy has become increasingly common, yet much remains unclear about the alliance and its importance for delivering mental health care via a digital format. To employ text-based digital therapies responsibly, more insight is needed into the type and strength of the therapeutic alliance online.
Methods: A systematic scoping review was performed searching four databases: Scopus, PsycINFO, Web of Science, and Wiley Online Library. A total of 23 studies were selected and data was extracted and tabulated to explore the characteristics of studies on text-based psychotherapy, measurements of the therapeutic alliance and associations of the alliance with treatment outcome.
Results: The therapeutic alliance in text-based digital interventions was studied with a variety of client groups, though mostly for clients diagnosed with anxiety and/or depression issues. Treatment modalities were predominantly internet-based cognitive behavioral therapy (ICBT) and tailored platforms for distinct client groups (e.g., PTSD). Almost all treatments used asynchronous text-based communication, such as e-mails and integrated messaging functions, which were mainly used to give feedback on tasks. For measurements, a version of the Working Alliance Inventory (WAI) was used in most studies. Measurements with the WAI or WAI- short form indicated a good therapeutic alliance with a weighted mean score of 5.66 (on a scale of 1 to 7) and a weighted standard deviation of 0.84. Relations between the therapeutic alliance and treatment outcomes were mostly positive, with many studies reporting significant associations (n = 8 out of 10) or significant effects of the therapeutic alliance on treatment outcomes (n = 5 out of 6).
Discussion: Our scoping review suggests that a good therapeutic alliance can be established in digital psychotherapy through text-based communication, and shows support for a positive relationship between the alliance and treatment outcomes. These findings illustrate that text-based online psychotherapy can be a responsible treatment option as far as the establishment of the therapeutic alliance is concerned. However, current measures of the therapeutic alliance might miss important aspects of the alliance in digital treatment, such as the presence of empathy or compassion.
The working alliance may be relevant in unguided smartphone-based interventions, but no validated measure exists. We evaluated the psychometric properties of the six-item Digital Working Alliance Inventory (DWAI) using a cross-sectional survey of meditation app users (n = 290) and the intervention arm of a randomized trial testing a smartphone-based meditation app (n = 314). Exploratory factor analysis suggested a single-factor solution which was replicated using longitudinal confirmatory factor analysis. The DWAI showed adequate internal consistency and test–retest reliability. Discriminant validity was supported by a lack of association with social desirability, psychological distress, and preference for a waitlist condition. Convergent validity was supported by positive associations with perceived app effectiveness and preference for an app condition. Supporting predictive validity, DWAI scores positively predicted self-reported and objective app utilization. When assessed at Weeks 3 or 4 of the intervention, but not earlier, DWAI scores predicted pre–post reductions in psychological distress.
The therapeutic alliance (TA), the relationship that develops between a therapist and a client/patient, is a critical factor in the outcome of psychological therapy. As mental health care is increasingly adopting digital technologies and offering therapeutic interventions that may not involve human therapists, the notion of a TA in digital mental health care requires exploration. To date, there has been some incipient work on developing measures to assess the conceptualization of a digital TA for mental health apps. However, the few measures that have been proposed have more or less been derivatives of measures from psychology used to assess the TA in traditional face-to-face therapy. This conceptual paper explores one such instrument that has been proposed in the literature, the Mobile Agnew Relationship Measure, and examines it through a human-computer interaction (HCI) lens. Through this process, we show how theories from HCI can play a role in shaping or generating a more suitable, purpose-built measure of the digital therapeutic alliance (DTA), and we contribute suggestions on how HCI methods and knowledge can be used to foster the DTA in mental health apps.
Background
During the COVID-19 pandemic, people have been encouraged to maintain social distance. Technology helps people schedule meetings as remote videoconferencing sessions rather than face-to-face interactions. Psychologists are in high demand because of an increase in stress as a result of COVID-19, and videoconferencing provides an opportunity for mental health clinicians to treat current and new referrals. However, shifting treatment from face-to-face to videoconferencing is not simple: both psychologists and clients miss in-person information cues, including body language.
Objective
This review proposes a new theoretical framework to guide the design of future studies examining the impact of a computer as a mediator of psychologist-client relationships and the influence of videoconferencing on the relationship process.
Methods
We conducted a literature review including studies focused on communication and key concepts of the therapeutic relationship and therapeutic alliance.
Results
Studies have reported that clients are generally satisfied with videoconference therapy in terms of the relationship with their therapists and the establishment of the therapeutic alliance. Conversely, studies indicate that psychologists continue to highlight difficulties in establishing the same quality of therapeutic relationship and therapeutic alliance. The contrasting experiences might underlie the differences in the type of emotional and cognitive work required by both actors in any therapy session; furthermore, the computer seems to take part in their interaction not only as a vehicle to transmit messages but also as an active part of the communication. A new model of interaction and relationship is proposed, taking into account the presence of the computer, along with further hypotheses.
Conclusions
It is important to consider the computer as having an active role in the client-psychologist relationship; thus, it is a third party to the communication that either assists or interferes with the interaction between psychologists and clients.
Background:
Digital mental health interventions offer unique advantages, and research indicates that these interventions are effective for a range of mental health concerns. Although these interventions are less established for individuals with serious mental illnesses, they demonstrate significant promise. A central consideration in traditional face-to-face therapies is the therapeutic alliance, whereas the nature of a digital therapeutic alliance and its relationship with outcomes requires further attention, particularly for individuals with serious mental illnesses.
Objective:
This narrative review aims to encourage further consideration and critical evaluation of the therapeutic alliance in digital mental health, specifically for individuals with serious mental illnesses.
Methods:
A narrative review was conducted by combining 3 main areas of the literature: the first examining the evidence for digital mental health interventions for serious mental illnesses, the second illuminating the nature and role of the therapeutic alliance in digital interventions, and the third surrounding practical considerations to enhance a digital therapeutic alliance.
Results:
Results indicated that a therapeutic alliance can be cultivated in digital interventions for those with serious mental illnesses, but that it may have unique, yet-to-be-confirmed characteristics in digital contexts. In addition, a therapeutic alliance appears to be less directly associated with outcomes in digital interventions than with those in face-to-face therapies. One possibility is that the digital therapeutic alliance is associated with increased engagement and adherence to digital interventions, through which it appears to influence outcomes. A number of design and implementation considerations may enhance the digital therapeutic alliance, including human support and technological features.
Conclusions:
More research is required to further understand the nature and specific role of a therapeutic alliance in digital interventions for serious mental illnesses, particularly in informing their design. This review revealed several key research priorities to advance the therapeutic alliance in digital interventions.
We investigated the potential role of first-session therapeutic alliance ratings to serve as an early marker of treatment outcome in youth mental health and addiction treatment. The present study is among the first to incorporate both a youths’ and a therapists’ perspective of the therapeutic alliance in order to maximize predictive value of the alliance for treatment outcome. One hundred and twenty-seven adolescents participated in a multi-site prospective naturalistic clinical cohort study, with assessments at baseline and at 4 months post-baseline. Main outcome measure was favorable or unfavorable treatment outcome status at 4-month follow-up. Early therapeutic alliance had a medium and robust association with treatment outcome for youth’ (b = 1.29) and therapist’ (b = 1.12) perspectives and treatment setting. Based on the two alliance perspectives four subgroups were distinguished. Incorporating the alliance-ratings from both perspectives provided a stronger predictor of treatment outcome than using one perspective. Youth with a strong alliance according to both perspectives had an eightfold odds of favorable treatment outcome compared with youth with a weak alliance according to both perspectives. The association between therapeutic alliance and treatment outcome in youth mental health and addiction treatment may be substantially stronger than earlier assumed when both a youths’ and therapists’ perspective on alliance is considered.
Background:
Compassion is a vital component to the achievement of positive health outcomes, particularly in mental health care. The rise of digital technologies may influence the delivery of compassionate care, and thus this relationship between compassion and digital health care needs to be better understood.
Objective:
This scoping review aimed to identify existing digital technologies being used by patients and health professionals in the delivery of mental health care, understand how digital technologies are being used in the delivery of compassionate mental health care, and determine the facilitators of and barriers to digital technology use among patients and health professionals in the delivery of compassionate mental health care.
Methods:
We conducted this scoping review through a search of Cumulative Index to Nursing and Allied Health Literature, Medical Literature Analysis and Retrieval System Online (MEDLINE), MEDLINE In-Process and EPub Ahead of Print, PsycINFO, and Web of Science for articles published from 1990 to 2019.
Results:
Of the 4472 articles screened, 37 articles were included for data extraction. Telemedicine was the most widely used technology by mental health professionals. Digital technologies were described as facilitating compassionate care and were classified using a conceptual model to identify each digital intersection with compassionate care. Facilitators of and barriers to providing compassionate care through digital technology were identified, including increased safety for providers, health care professional perceptions and abilities, and the use of picture-in-picture feedback to evaluate social cues.
Conclusions:
Implementing digital technology into mental health care can improve the current delivery of compassionate care and create novel ways to provide compassion. However, as this is a new area of study, mental health professionals and organizations alike should be mindful that compassionate human-centered care is maintained in the delivery of digital health care. Future research could develop tools to facilitate and evaluate the enactment of compassion within digital health care.
The digital revolution is evolving at an unstoppable pace. Alongside the unprecedented explosion of digital technology facilities and systems, mental health care is under greater pressure than ever before. With its emphasis on big data, computing power, mobile technology, and network information, digital technology is set to transform health care delivery. This article reviews the field of digital health technology assessment and intervention primarily in secondary service mental health care, including the barriers and facilitators to adopting and implementing digitally mediated interventions in service delivery. We consider the impact of digitally mediated communication on human interaction and its potential impact on various mental states such as those linked to mood, anxiety but also well‐being. These developments point to a need for both theory‐ and data‐driven approaches to digital health care. We argue that, as developments in digital technology are outpacing the evaluation of rigorous digital health interventions, more advanced methodologies are needed to keep up with the pace of digital technology development. The need for co‐production of digital tools with and for people with chronic and mental health difficulties, and implications of digital technology for psychotherapy practice, will be central to this development.
Practitioner points
Mental health problems are one of the main causes of global and societal burden and are a growing public health.
People with mental health problems around the world have limited, if any, chance of accessing psychological help at all.
Technological innovations and solutions are being considered in an attempt to address the size and scale of the mental health crisis worldwide.
Digital platforms allow people to self‐monitor and self‐manage in a way that face‐to‐face/paper‐based methods of assessment have up until now not allowed.
We provide examples of digital tools that are being developed and used in the secondary setting and identify a number of challenges in the digital health field that require careful consideration.
Background
As mental healthcare expands to smartphone apps and other technologies that may offer therapeutic interventions without a therapist involved, it is important to assess the impact of non-traditional therapeutic relationships.
Aims
To determine if there were any meaningful data regarding the digital therapeutic alliance in smartphone interventions for serious mental illnesses.
Method
A literature search was conducted in four databases (PubMed, PsycINFO, Embase and Web of Science).
Results
There were five studies that discuss the therapeutic alliance when a mobile application intervention is involved in therapy. However, in none of the studies was the digital therapeutic alliance the primary outcome. The studies looked at different mental health conditions, had different duration of technology use and used different methods for assessing the therapeutic alliance.
Conclusions
Assessing and optimising the digital therapeutic alliance holds the potential to make tools such as smartphone apps more effective and improve adherence to their use. However, the heterogeneous nature of the five studies we identified make it challenging to draw conclusions at this time. A measure is required to evaluate the digital therapeutic alliance.
Open access: http://psycnet.apa.org/fulltext/2018-23951-001.pdf Abstract: The alliance continues to be one of the most investigated variables related to success in psychotherapy irrespective of theoretical orientation. We define and illustrate the alliance (also conceptualized as therapeutic alliance, helping alliance or working alliance) and then present a meta-analysis of 295 independent studies that covered more than 30,000 patients (published between 1978 and 2017) for face-to-face psychotherapy as well as internet-based psychotherapy. The relation of the alliance and treatment outcome was investigated using three-level meta- analysis with random-effects restricted maximum-likelihood estimators. The overall alliance- outcome association for face-to-face psychotherapy was r = .278 (95% CIs [.256, .299], p < .0001; equivalent of d = .579). There was heterogeneity among the ESs, and 2% of the 295 ESs indicated negative correlations. The correlation for internet-based psychotherapy was approximately the same (viz., r = .275, k = 23). These results confirm the robustness of the positive relation between the alliance and outcome. This relation remains consistent across assessor perspectives, alliance and outcome measures, treatment approaches, patient characteristics, and countries. The article concludes with causality considerations, research limitations, diversity considerations, and therapeutic practices.
Keywords: therapeutic alliance, psychotherapy relationship, working alliance, meta-analysis, psychotherapy outcome, face-to-face therapy, internet-based therapy
Background:
Digital health interventions in the form of smartphone apps aim to improve mental health and enable people access to support as and when needed without having to face the stigma they may experience in accessing services. If we are to evaluate mobile health (mHealth) apps and advance scientific understanding, we also need tools to help us understand in what ways mHealth interventions are effective or not. The concept of therapeutic alliance, a measure of the quality of the relationship between a health care provider and a service user, is a key factor in explaining the effects of mental health interventions. The Agnew Relationship Measure (ARM) is a well-validated measure of therapeutic alliance in face-to-face therapy.
Objective:
This study presented the first attempt to (1) explore service users' views of the concept of relationship within mHealth mental health interventions and (2) adapt a well-validated face-to-face measure of therapeutic alliance, the Agnew Relationship Measure (ARM), for use with mHealth interventions.
Methods:
In stage 1, we interviewed 9 mental health service users about the concept of therapeutic alliance in the context of a digital health intervention and derived key themes from interview transcripts using thematic analysis. In stage 2, we used rating scales and open-ended questions to elicit views from 14 service users and 10 mental health staff about the content and face validity of the scale, which replaced the word "therapist" with the word "app." In stage 3, we used the findings from stages 1 and 2 to adapt the measure with the support of a decision-making algorithm about which items to drop, retain, or adapt.
Results:
Findings suggested that service users do identify relationship concepts when thinking about mHealth interventions, including forming a bond with an app and the ability to be open with an app. However, there were key differences between relationships with health professionals and relationships with apps. For example, apps were not as tailored and responsive to each person's unique needs. Furthermore, apps were not capable of portraying uniquely human-like qualities such as friendliness, collaboration, and agreement. We made a number of changes to the ARM that included revising 16 items; removing 4 items due to lack of suitable alternatives; and adding 1 item to capture a key theme derived from stage 1 of the study ("The app is like having a member of my care team in my pocket").
Conclusions:
This study introduces the mHealth version of the ARM, the mARM, that has good face and content validity. We encourage researchers to include this easy-to-use tool in digital health intervention studies to gather further data about its psychometric properties and advance our understanding of how therapeutic alliance influences the efficacy of mHealth interventions.
Trial registration:
International Standard Randomized Controlled Trial Number (ISRCTN) 34966555; http://www.isrctn.com/ISRCTN34966555 (Archived by WebCite at http://www.webcitation.org/6ymBVwKif).
Background
There are an increasing number of mobile apps available for adolescents with mental health problems and an increasing interest in assimilating mobile health (mHealth) into mental health services. Despite the growing number of apps available, the evidence base for their efficacy is unclear.
Objective
This review aimed to systematically appraise the available research evidence on the efficacy and acceptability of mobile apps for mental health in children and adolescents younger than 18 years.
Methods
The following were systematically searched for relevant publications between January 2008 and July 2016: APA PsychNet, ACM Digital Library, Cochrane Library, Community Care Inform-Children, EMBASE, Google Scholar, PubMed, Scopus, Social Policy and Practice, Web of Science, Journal of Medical Internet Research, Cyberpsychology, Behavior and Social Networking, and OpenGrey. Abstracts were included if they described mental health apps (targeting depression, bipolar disorder, anxiety disorders, self-harm, suicide prevention, conduct disorder, eating disorders and body image issues, schizophrenia, psychosis, and insomnia) for mobile devices and for use by adolescents younger than 18 years.
Results
A total of 24 publications met the inclusion criteria. These described 15 apps, two of which were available to download. Two small randomized trials and one case study failed to demonstrate a significant effect of three apps on intended mental health outcomes. Articles that analyzed the content of six apps for children and adolescents that were available to download established that none had undergone any research evaluation. Feasibility outcomes suggest acceptability of apps was good and app usage was moderate.
Conclusions
Overall, there is currently insufficient research evidence to support the effectiveness of apps for children, preadolescents, and adolescents with mental health problems. Given the number and pace at which mHealth apps are being released on app stores, methodologically robust research studies evaluating their safety, efficacy, and effectiveness is promptly needed.
Background:
Studies of Internet-delivered psychotherapies suggest that clients report development of a therapeutic alliance in the Internet environment. Because a majority of the interventions studied to date have been therapist-assisted to some degree, it remains unclear whether a therapeutic alliance can develop within the context of an Internet-delivered self-guided intervention with no therapist support, and whether this has consequences for program outcomes.
Objective:
This study reports findings of a secondary analysis of data from 90 participants with mild-to-moderate depression, anxiety, and/or stress who used a fully automated mobile phone and Web-based cognitive behavior therapy (CBT) intervention called "myCompass" in a recent randomized controlled trial (RCT).
Methods:
Symptoms, functioning, and positive well-being were assessed at baseline and post-intervention using the Depression, Anxiety and Stress Scale (DASS), the Work and Social Adjustment Scale (WSAS), and the Mental Health Continuum-Short Form (MHC-SF). Therapeutic alliance was measured at post-intervention using the Agnew Relationship Measure (ARM), and this was supplemented with qualitative data obtained from 16 participant interviews. Extent of participant engagement with the program was also assessed.
Results:
Mean ratings on the ARM subscales were above the neutral midpoints, and the interviewees provided rich detail of a meaningful and collaborative therapeutic relationship with the myCompass program. Whereas scores on the ARM subscales did not correlate with treatment outcomes, participants' ratings of the quality of their emotional connection with the program correlated significantly and positively with program logins, frequency of self-monitoring, and number of treatment modules completed (r values between .32-.38, P≤.002). The alliance (ARM) subscales measuring perceived empowerment (r=.26, P=.02) and perceived freedom to self-disclose (r=.25, P=.04) also correlated significantly in a positive direction with self-monitoring frequency.
Conclusions:
Quantitative and qualitative findings from this analysis showed that a positive therapeutic alliance can develop in the Internet environment in the absence of therapist support, and that components of the alliance may have implications for program usage. Further investigation of alliance features in the Internet environment and the consequences of these for treatment outcomes and user engagement is warranted.
Trial registration:
Australian New Zealand Clinical Trials Registry Number (ACTRN): 12610000625077; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=335772&isReview=true (Archived by WebCite at http://www.webcitation.org/6efAc5xj4).
Structural equation modeling (SEM) has a long history of representing models graphically as path diagrams. This article presents the freely available semPlot package for R, which fills the gap between advanced, but time-consuming, graphical software and the limited graphics produced automatically by SEM software. In addition, semPlot offers more functionality than drawing path diagrams: It can act as a common ground for importing SEM results into R. Any result usable as input to semPlot can also be represented in any of the 3 popular SEM frameworks, as well as translated to input syntax for the R packages sem (Fox, Nie, & Byrnes, 2013) and lavaan (Rosseel, 2012). Special considerations are made in the package for the automatic placement of variables, using 3 novel algorithms that extend the earlier work of Boker, McArdle, and Neale (2002). The article concludes with detailed instructions on these node-placement algorithms.
Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software pack-ages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the develop-ment of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
Internet-delivered self-help with minimal therapist guidance has shown promising results for a number of diagnoses. Most of the evidence comes from studies evaluating standardized disorder-specific treatments. A recent development in the field includes transdiagnostic and tailored Internet-based treatments that address comorbid symptoms and a broader range of patients. This study evaluated an Internet-based tailored guided self-help treatment, which targeted symptoms of social anxiety disorder, panic disorder with or without agoraphobia, and generalized anxiety disorder. The tailored treatment was compared both with standardized disorder-specific Internet-based treatment and with a wait-list control group. Both active treatment conditions were based on cognitive-behavioral therapy and lasted for 8 weeks. A total of 132 individuals meeting diagnostic criteria for at least one of the anxiety disorders were randomly assigned to 1 of the 3 conditions. Both treatment groups showed significant symptom reductions as compared with the wait-list control group on primary disorder-unspecific measures of anxiety, depression, and general symptomatology and on secondary anxiety disorder-specific measures. Based on the intention-to-treat sample, mean between-group effect sizes were d = 0.80 for the tailored treatment and d = 0.82 for the standardized treatment, versus wait-list controls. Treatment gains were maintained at 6-month follow-up. No differences were found between the 2 active treatment conditions on any of the measures, including a telephone-administered diagnostic interview conducted at posttreatment. The findings suggest that both Internet-based tailored guided self-help treatments and Internet-based standardized treatments are promising treatment options for several anxiety disorders. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
An approximate test and confidence interval for coefficient alpha are derived. The approximate test and confidence interval are then used to derive closed-form sample size formulas. The sample size formulas can be used to determine the sample size needed to test coefficient alpha with desired power or to estimate coefficient alpha with desired precision. The sample size formulas closely approximate the sample size requirements for an exact confidence interval or an exact test.
The benefits of self-monitoring on symptom severity, coping, and quality of life have been amply demonstrated. However, paper and pencil self-monitoring can be cumbersome and subject to biases associated with retrospective recall, while computer-based monitoring can be inconvenient in that it relies on users being at their computer at scheduled monitoring times. As a result, nonadherence in self-monitoring is common. Mobile phones offer an alternative. Their take-up has reached saturation point in most developed countries and is increasing in developing countries; they are carried on the person, they are usually turned on, and functionality is continually improving. Currently, however, public conceptions of mobile phones focus on their use as tools for communication and social identity. Community attitudes toward using mobile phones for mental health monitoring and self-management are not known.
The objective was to explore community attitudes toward the appropriation of mobile phones for mental health monitoring and management.
We held community consultations in Australia consisting of an online survey (n = 525), focus group discussions (n = 47), and interviews (n = 20).
Respondents used their mobile phones daily and predominantly for communication purposes. Of those who completed the online survey, the majority (399/525 or 76%) reported that they would be interested in using their mobile phone for mental health monitoring and self-management if the service were free. Of the 455 participants who owned a mobile phone or PDA, there were no significant differences between those who expressed interest in the use of mobile phones for this purpose and those who did not by gender (χ2(1), = 0.98, P = .32, phi = .05), age group (χ2(4), = 1.95, P = .75, phi = .06), employment status (χ2(2), = 2.74, P = .25, phi = .08) or marital status (χ2(4), = 4.62, P = .33, phi = .10). However, the presence of current symptoms of depression, anxiety, or stress affected interest in such a program in that those with symptoms were more interested (χ(2) (1), = 16.67, P < .001, phi = .19). Reasons given for interest in using a mobile phone program were that it would be convenient, counteract isolation, and help identify triggers to mood states. Reasons given for lack of interest included not liking to use a mobile phone or technology, concerns that it would be too intrusive or that privacy would be lacking, and not seeing the need. Design features considered to be key by participants were enhanced privacy and security functions including user name and password, ease of use, the provision of reminders, and the availability of clear feedback.
Community attitudes toward the appropriation of mobile phones for the monitoring and self-management of depression, anxiety, and stress appear to be positive as long as privacy and security provisions are assured, the program is intuitive and easy to use, and the feedback is clear.
The multitrait-multimethod ( MTMM) design is often used in test validation research to disentangle problems due to shared method variance. However, MTMM research requires extensive data collection that may be prohibitive in clinical settings. Furthermore, interpretation of MTMM data can be ambiguous and misleading. In the current article, maximum-likelihood confirmatory factor analysis ( CFA) is presented as a means for less ambiguous interpretation of complete and incomplete MTMM designs. Confirmatory Factor analysis is applied to four data sets that represent four designs: monotrait-monomethod, multitrait-monomethod, monotrait-multimethod, and multitrait-multimethod. In all four cases, CFA results provided more rigorous support of the original authors’ positions and provided valuable supplemental findings as well. Additionally, CFA was applied to an artificial data set. Intuitive interpretations of the artificial data were compared with the results of the CFA. The results showed that the intuitive approach can lead to highly spurious conclusions regarding convergent and discriminant validity.
We used a new instrument, the Agnew Relationship Measure (ARM), to examine the alliance's dimensionality and to construct scales for use in future studies.
We studied the alliance as reported on the ARM by both clients and therapists in the Second Sheffield Psychotherapy Project, a randomized comparison of two contrasting time-limited psychotherapies for depression.
Clients (N = 95) and therapists (N = 5) completed parallel forms of the (ARM) after every session (N = 1120).
Five scales were constructed, based on results of simultaneous components analyses and considerations of conceptual coherence and comparability across client and therapist perspectives.
Bond, partnership, and confidence overlapped statistically (consistent with previous studies), but there are conceptual and empirical reasons for retaining the distinctions. Openness represented a relatively independent dimension. The client initiative scale had low internal consistency but the items may have value for future investigations.
Introduction: Reappraisal is one of the highly modifiable resilience factors and an important emotion regulation strategy. Reappraisal training can be delivered via mobile apps; however, such apps have typically combined reappraisal with other techniques. To address this gap, we developed ReApp, which engages users solely in reappraisal. Methods: For two trials, we invited 40 and 95 young adults with low levels of reappraisal skills. Participants were randomized into either control (CG) or intervention group (IG). The CG had access only to the Ecological Momentary Assessment component of the app, while the IG could also access the reappraisal training. We analyzed the self-report data using linear mixed models.Results: In both trials, adherence was high. Trial 1 revealed that only participants with very low reappraisal skills at baseline benefited from ReApp. This outcome was replicated in Trial 2 but there were no significant differences between the groups in the follow-up in mental health symptoms severity.Discussion: High adherence suggests that participants found it easy to integrate ReApp into their daily routines. Furthermore, ReApp successfully increased reappraisal in individuals with low level of reappraisal skills. Future studies will focus on assessing the efficacy of EMI-delivered reappraisal training on healthy and clinical populations.
The alliance-outcome relationship has been consistently linked to positive treatment outcomes irrespective of psychotherapy modality. However, beyond its general links to favorable treatment outcomes, it is less clear whether the alliance is a specific mediator of change and thus a possible mechanism underlying psychotherapy response. This systematic review evaluated research examining the alliance as a potential mediator of symptom change, reviewing study characteristics of 37 relevant articles examining the alliance-outcome relationship and the extent to which these studies met recommended criteria for mechanistic research. Alliance mediated therapeutic outcomes in 70.3% of the studies. We observed significant heterogeneity across studies in terms of methodology, including timing of alliance assessment, study design, constructs used in mediation models, and analytic approaches. Building on recent methodological advancements, we propose directions for future research examining the putative mediational role of alliance, such as greater uniformity in and attention to study design and statistical methodology. This review highlights the importance of alliance in therapeutic change and discusses how adhering to requirements for process research will improve our ability to more precisely estimate how and to what extent alliance drives therapeutic change.
Purpose of review:
The purpose of this update is to provide an overview of the breadth of research studies published from April 2017 to April 2018 on mobile-based interventions for mental health, with a special emphasis on smartphone-based interventions.
Recent findings:
Several studies during the review period have described the process of applying user-centred design in the development of mental health apps and novel approaches to enhance user-engagement. Studies on consumer perspectives indicate largely positive findings about open-ness to utilize mental health apps. There is a scarcity of similar studies on health providers. Efficacy studies have provided evidence for apps for a variety of psychiatric disorders. There are fewer studies on preventive and promotive interventions. Although a plethora of mental health apps is available for public, most have not undergone scientific evaluation. Many well researched apps are not accessible to public. The potential of smartphone technology in enhancing healthcare service delivery in low-resource settings has also been examined in a few studies.
Summary:
Evidence for acceptability, feasibility and efficacy of mobile-based mental health interventions for facilitating recovery is on the rise. More research is needed on implementation and integration of these interventions in diverse real-world clinical and community contexts.
Psychotherapy services are limited in remote and rural areas in Australia and across the globe.
Videoconferencing has become well established as a feasible and acceptable mode of psychological treatment
delivery. Therapeutic alliance (TA) is an essential factor underlying successful therapy across therapeutic
models. In order to determine the state of knowledge regarding TA in psychotherapy via videoconferencing, a
literature review was conducted on research studies that formally measured TA as primary, secondary or tertiary
outcome measures over the past 23 years. The databases searched were Medline, PsycArticles, PsycINFO,
PsycEXTRA and EMBASE. Searching identified 9915 articles that measured satisfaction, acceptability or
therapeutic rapport, of which 23 met criteria for the review. Three studies were carried out in Australia, 11 in
USA, 4 in Canada, 3 in Scotland and 2 in England. Studies overwhelmingly supported the notion that TA
can be developed in psychotherapy by videoconference, with clients rating bond and presence at least equally as
strongly as in-person settings across a range of diagnostic groups. Therapists also rated high levels of TA, but
often not quite as high as that of their clients early in treatment. The evidence was examined in the context of
important aspects of TA, including bond, presence, therapist attitudes and abilities, and client attitudes and
beliefs. Barriers and facilitators of alliance were identified. Future studies should include observational measures
of bond and presence to supplement self-report.
Barrett's (2007) article on "adjudging model fit" raises some important issues concerning the use of global fit indices to justify weak structural equation models, and recommends prohibition of future use of such indices. In this commentary, I critique Barrett's presentation, and show that his recommendations are (a) unnecessarily regressive, and (b) likely to be ignored. Then I suggest a constructive afternative in line with the spirit of his concerns. (c) 2006 Elsevier Ltd. All rights reserved.
Meta-analyses have consistently concluded that a positive therapeutic alliance is associated with better clinical outcomes and progress. To date, however, very few studies have focused on sociodemographic or clinical patient characteristics as moderators of alliance.
A multicenter longitudinal treatment outcome study was conducted to investigate the associations of patient and clinician perceptions of the therapeutic alliance with improvement in depression, and to investigate whether these associations were influenced by sociodemographic or clinical characteristics of the patient. Clinician-rated Montgomery Åsberg Depressive Rating Scale scores and both patient- and therapist-rated Helping Alliance Questionnaire (HAQ-I) scores were obtained from 567 outpatients with major depressive disorder who received 6 months of combined psycho- and pharmacotherapy.
Multilevel repeated-measures analyses indicated that patient- and therapist-rated HAQ-I scores, 4 weeks after treatment began, positively predicted subsequent clinical change, controlling for the effect of early improvement and a range of patient characteristics. Next to alliance, early improvement, initial depressive symptom severity, a history of psychiatric disorders, and occupational status affected the rate of clinical improvement. Personality pathology comorbidity, marital and occupational status, and the atypical character of the major depressive episode (MDE) moderated the alliance-outcome relationship, depending on the informant (patient or therapist) of therapeutic alliance.
The present findings suggest that therapist and patient ratings of therapeutic alliance predict therapeutic progress, and that this relation may be moderated by client characteristics, including personality pathology comorbidity, marital status, occupational status, and the atypical character of the MDE.
This pilot study aimed to explore the clinical outcomes and therapeutic relationship for clients of an adult mental health service using Beating the Blues, a computerised cognitive behaviour therapy (CCBT) package. Sixteen participants completed the programme and reported a significant reduction in Beck Depression Inventory scores posttreatment. Participants' mean item ratings on the relationship measure were above the neutral midpoint, but no association was found between the therapeutic relationship and outcome. The results are discussed in terms of the utility of CCBT as part of a stepped-care model and how further research might usefully explore the nature of the relationship formed between clients and CCBT programmes.
With the increase in the number of multinational and multicultural research projects, the need to adapt health status measures for use in other than the source language has also grown rapidly. 1,4,27 Most questionnaires were developed in English-speaking countries, 11 but even within these countries, researchers must consider immigrant populations in studies of health, especially when their exclusion could lead to a systematic bias in studies of health care utilization or quality of life. 9,11 The cross-cultural adaptation of a health status selfadministered questionnaire for use in a new country, culture, and/or language necessitates use of a unique method, to reach equivalence between the original source and target versions of the questionnaire. It is now recognized that if measures are to be used across cultures, the items must not only be translated well linguistically, but also must be adapted culturally to maintain the content validity of the instrument at a conceptual level across different cultures. 6,11‐13,15,24 Attention to this level of detail allows increased confidence that the impact of a disease or its treatment is described in a similar manner in multinational trials or outcome evaluations. The term “cross-cultural adaptation” is used to encompass a process that looks at both language (translation) and cultural adaptation issues in the process of preparing a questionnaire for use in another setting. Cross-cultural adaptations should be considered for several different scenarios. In some cases, this is more obvious than in others. Guillemin et al 11 suggest five different examples of when attention should be paid to this adaptation by comparing the target (where it is going to be used) and source (where it was developed) language and culture. The first scenario is that it is to be used in the same language and culture in which it was developed. No adaptation is necessary. The last scenario is the opposite extreme, the application of a questionnaire in a different culture, language and country—moving the Short Form 36-item questionnaire from the United States (source) to Japan (target) 7 which would necessitate translation and cultural adaptation. The other scenarios are summarized in Table 1 and reflect situations when some translation and/or adaptation is needed. The guidelines described in this document are based on a review of cross-cultural adaptation in the medical, sociological, and psychological literature. This review led to the description of a thorough adaptation process designed to maximize the attainment of semantic, idiomatic, experiential, and conceptual equivalence between the source and target questionnaires. 13 . Further experience in cross-cultural adaptation of generic and diseasespecific instruments and alternative strategies driven by different research groups 18 have led to some refinements
Cronbach's a is the most widely used index of the reliability of a scale. However, its use and interpretation can be subject to a number of errors. This article discusses the historical development of a from other indexes of internal consistency (split-half reliability and Kuder-Richardson 20) and discusses four myths associated with a: (a) that it is a fixed property of the scale, (b) that it measures only the internal consistency of the scale, (c) that higher values are always preferred over lower ones, and (d) that it is restricted to the range of 0 to 1. It provides some recommendations for acceptable values of a in different situations.
In the past two decades, a number of studies investigating the role of the therapeutic alliance in drug treatment have been published and it is timely that their findings are brought together in a comprehensive review.
This paper has two principal aims: (1) to assess the degree to which the relationship between drug user and counsellor predicts treatment outcome and (2) to examine critically the evidence on determinants of the quality of the alliance.
Peer-reviewed research located through the literature databases Medline, PsycInfo and Ovid Full Text Mental Health Journals using predefined search-terms and published in the past 20 years is considered. Further papers were identified from the bibliographies of relevant publications.
A key finding is that the early therapeutic alliance appears to be a consistent predictor of engagement and retention in drug treatment. With regard to other treatment outcomes, the early alliance appears to influence early improvements during treatment, but it is an inconsistent predictor of post-treatment outcomes. There is relatively little research on the determinants of the alliance. In studies that are available, clients' demographic or diagnostic pre-treatment characteristics did not appear to predict the therapeutic alliance, whereas modest but consistent relationships were reported for motivation, treatment readiness and positive previous treatment experiences.
The therapeutic alliance plays an important role in predicting drug treatment process outcomes, but too little is known about what determines the quality of the relationship between drug users and counsellors.
Nurse researchers typically provide evidence of content validity for instruments by computing a content validity index (CVI), based on experts' ratings of item relevance. We compared the CVI to alternative indexes and concluded that the widely-used CVI has advantages with regard to ease of computation, understandability, focus on agreement of relevance rather than agreement per se, focus on consensus rather than consistency, and provision of both item and scale information. One weakness is its failure to adjust for chance agreement. We solved this by translating item-level CVIs (I-CVIs) into values of a modified kappa statistic. Our translation suggests that items with an I-CVI of .78 or higher for three or more experts could be considered evidence of good content validity.
Providing care in innovative ways
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Sample size calculator. wnarifin.github.io. 2022
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Computing power and minimum sample size for RMSEA. Vanderbilt University
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