Bob is an extremely needy patient with high levels of anxiety.
When Dr.
Leo Marvin and his patient, Bob Wiley. Dr. Marvin leaves for vacation, Bob decides to follow him and his family. Participants were 49 people recruited online via the Black Dog Institute’s website and volunteer research register for a proof of concept study assessing the feasibility and acceptability of the myCompass intervention.
Eligibility criteria included.
Owning a ‘internet enabled’ mobile phone; having access to a desktop computer with internet capability; and having a valid email address, Australian resident aged 18 to 75 years. Initial sample was 70 dot 5percent female with a mean age of 38 dot 2 years. Following a ‘7week’ delay, waitlist participants received full access to the myCompass program for seven weeks.
Then the program was designed to be interesting but contained no management advice or therapeutic strategies.
Attention control participants received a control mental health program with high face validity that was matched to the myCompass intervention on duration and mode of delivery.
Participants in the myCompass condition were able to use the program, ad libitum, for seven weeks. Previous reviews support a mediating role of cognitive variables in recovery from mental health problems, and, more recently, a construct about ‘selfefficacy’, namely ‘perceived control’, is shown to predict outcomes of online ‘therapist assisted’ CBT for depression. To our knowledge, no research has examined whether symptom and functional outcomes in online ‘self help’ interventions are associated with changes in ‘selfefficacy’ beliefs over the course of treatment, and pretreatment self efficacy remains largely unexplored as a potential determinant of therapeutic gains in online CBT interventions.
Increased ‘self efficacy’ beliefs have also been linked with more effective emotion regulation and psychosocial functioning.
Online psychotherapy is clinically effective yet why, how, and for whom the effects are greatest remain largely unknown.
In the present study, we examined whether mental health ‘selfefficacy’, a construct derived from Bandura’s Social Learning Theory, influenced symptom and functional outcomes of a really new mobile phone and web based psychotherapy intervention for people with mildtomoderate depression, anxiety and stress. Selfefficacy is likely, therefore, to be an important factor contributing to symptom and functional gains within the context of online interventions, particularly those with minimal therapist input. Just think for a moment. As well as the ongoing practice and implementation of therapeutic skills, it’s for any longer being that such interventions require the active cognitive and behavioural involvement of the individual often in the face of challenges and difficult experiences. Theoretical models posit that selfefficacy impacts therapeutic outcomes by affecting individuals’ decisions to change their behaviour, and by influencing how much effort people for a while they will persist in the face of obstacles and aversive experiences.
I am sure that the authors gratefully acknowledge the participants for their involvement in the research, and the Australian Government Department of Health and Ageing for funding the development of the myCompass program and these research studies.
JP for salary support and GP for research support.
No individuals employed or contracted by the funders played any role in the design, data collection, statistical analysis, or decision to publish these studies, nor preparation of this manuscript. Essentially, jP and GP are also grateful to the National Health and Medical Research Council. Nevertheless, in the present study, restricted maximum likelihood was used to estimate model parameters, and error degrees of freedom were calculated using Satterthwaite’s approximation. In MMRM, no participant is removed from the for awhile being that all available data are used to obtain parameter estimates. We examined our data using two techniques, statistical methods for testing mediation vary. Initially, Baron and Kenny’s criteria were examined sequentially in a series of mixed models repeated measures procedures. Analyses assumed a compound symmetric structure, in line with Fairclough’s recommendation that the covariance structure be restricted in situations where attrition is high.
I am sure that the finding that MHSE enhancement mediated symptom improvement suggests that precise targeting of MHSE may have the potential to increase the therapeutic potency and clinical efficiency of online interventions for common mental health problems.
Research has shown that selfefficacy can be reinforced via a range of information sources, including performance mastery, verbal persuasion and social influence, vicarious learning, and emotional arousal, and studies show that ‘selfmanagement’ programs incorporating these strategies produce more favourable physical health outcomes,.
In the case of myCompass, Bandura’s SLT may provide an useful theoretical basis upon which the program’s self efficacy promoting content and functions can be enhanced. In both sets of analyses, MHSE reflected change from baseline to post intervention, and was computed by subtracting baseline scores from ‘post intervention’ scores. I’m sure it sounds familiar. Baseline scores on the outcome variable of interest were entered as covariates in all models. That’s right! An initial FA of the six MHSES items yielded a single factor solution accounting for 67 of the cumulative variance.
By the way, a CFA testing the validity of the factor structure derived for the MHSES in Study I yielded a chisquare of 146 dot 7, and the following fit indices.
Root mean square error of approximation = 15; and standardised root mean square residual = Whereas the CFI, TLI and SRMR all satisfied conventional guidelines for acceptable model fit, the RMSEA was larger than the desirable upper limit of 08 -, TuckerLouis Index = 91.
Cronbach’s alpha for the MHSES was 91. In light of recent evidence questioning the validity of the RMSEA in models with low degrees of freedom, and given further evidence of the model’s adequacy in the sort of significant parameter estimates across all scale items, we judged that there was sufficient evidence confirming the single factor structure of the MHSES.
Self efficacy is a taskspecific construct that varies across distinct groups of behaviours.
Developed and validated for use in people with severe mental illness, Carpinello et al.’s Mental Health Confidence Scale relies heavily on recoveryrelated items, including items referring to mental illness diagnosis and treatment, and should be inappropriate for people with symptoms in the mildtomoderate range who are unlikely to consider themselves unwell, meet diagnostic criteria or seek treatment.
In contrast with the plethora of selfefficacy scales for physical health and lifestyle improvement, we were able to locate only one scale measuring people’s confidence in managing mental health problems. Accordingly, to investigate the effects of ‘selfefficacy’ on therapeutic gains in online psychological interventions, we developed and psychometrically evaluated a tally new measure of MHSE for common mental health problems, the Mental Health Selfefficacy Scale.
Therefore the authors declare that they have no competing interests.
Primary care of people with symptoms in this range is often complicated by the fact that providers, especially general practitioners, face difficulties identifying which of their patients will take up and benefit from the various treatment options available.
At minimum, our findings suggest that screening of patients using a short, simple, measure of MHSE most certainly to benefit from selfhelp interventions delivered online. And therefore the analyses also indicated a subset of individuals with symptoms in the mild to moderate range who may indeed benefit most from webbased psychotherapeutic interventions, namely those with low MHSE. Whenever in line with Baron and Kenny, mHSE will satisfy criteria for mediation if. Baron and Kenny’s causal steps framework is still the most widely used approach to testing mediation in the social sciences. Notice that findings of the MMRM procedures are presented first.
With data showing that symptom improvement and functional gains were greatest for people who used the myCompass intervention, we have previously provided support for Baron and Kenny’s first criterion.
All authors read and approved the final manuscript.
JP conceived and designed the study, contributed to questionnaire development, supervised the data collection, participated in the data analysis and interpretation of results, and carried out critical revision for intellectual content; MRB undertook data collection and revised the manuscript critically; AW assisted with data collection, statistical analysis and interpretation of results, and revised the manuscript for intellectual content; GP was involved in the concept and design of the study and revised the manuscript critically; VM participated in the design and concept of the study, questionnaire development and manuscript review; VH was involved in the concept and design of the study, questionnaire development, and revision of the manuscript; HC participated in manuscript preparation and revision for intellectual content; DH P was involved in the concept and design of the study, questionnaire development, statistical analysis and manuscript revision, JC undertook data collection, and performed the statistical analyses and data interpretation, and drafted the manuscript.
In the present study, we provide preliminary data on a really new scale measuring people’s confidence in managing problems related to their mental health, the MHSES.
We also explored hypotheses derived from Bandura’s SLT.
Therefore second, that program outcomes would differ between people with high and low levels of ‘preintervention’ MHSE. Basically the RCT was registered as Australian New Zealand Clinical Trials Registry ACTRN12610000625077. For both studies, written consent was provided by study participants and ethical approval was obtained from the Human Research Ethics Committee at UNSW Australia. We report on outcomes of two studies. MHSES, and secondary analysis of data from a recently completed RCT to examine the effects of MHSE on symptom and functional outcomes of a fullyautomated mobile phone and web intervention.
Australian New Zealand Clinical Trials Registry ACTRN12610000625077 Online selfmanagement of depression and anxiety has evolved as a popular, clinically effective and costefficient public health solution to reducing the personal and societal burden associated with unmet treatment need,.
Rates of adherence with these interventions, that are characteristically low, can be improved by incorporating program content and functions that increase therapeutic efficiency by targeting intervening processes directly.
Grounded predominantly in cognitive behaviour therapy, and increasingly incorporating other therapeutic approaches, online psychological interventions additional set of MMRM procedures was conducted, that included all possible main effects and interactions between treatment condition, time, and baseline MHSE, to explore the potential moderating effect of MHSE. So it’s likely that differences exist in the putative mediators of mental health symptom versus functional outcomes in web based interventions, with important implications for designing program content and functions, as suggested by our data.
Multiple mediator models in for awhile side’ other theoretically relevant mediator variables may be studied.
Lots of us know that there are other variables from Bandura’s SLT, including outcome expectancies and personal goals, that may combine with such cognitive variables as attitudes, thoughts, and attributional styles, to affect outcomes of face to face and online therapies.
MHSE was only one potential mediator considered in this study, thereby precluding us from commenting on its relative utility in predicting symptom and functional outcomes in ‘webbased’ psychotherapies. With a mean age of 38 dot 9 years, a set of Bonferroni adjusted interaction contrasts constructed to estimate between group differences in mean change from baseline to post intervention showed significantly greater improvement in MHSE for participants in the mobile phone and web intervention condition than the AC. Employed and married. Participants were randomised after baseline to one of three conditions. Certainly, compass, an attention control condition. With the between subjects variable of group and the withinsubjects variable of time, significant correlations in the expected direction between the MHSES and DASS Depression, Anxiety by 2 repeated measures model, yielded a significant interaction effect of treatment and measurement occasion for scores on the MHSES. Compass is a fullyautomated public health CBT intervention for common mental health problems that is delivered via the internet to people’s mobile phones and desktop computers.
Study I reports data collected from participants at baseline. Participants completed online questionnaires before and after using the myCompass program for six weeks. In Study I, we showed that MHSE is a potential psychological mechanism through which a fully automated, mobile phone and web psychotherapeutic intervention affects symptom and functional outcomes. Besides, the potential role of perceived ‘selfefficacy’ in determining outcomes of mental health interventions is testable now that a straightforward, reliable and valid measure of MHSE is available. Nonetheless, it also appears that differences in pretreatment levels of MHSE may have important implications for understanding differential responses to treatment. You can find a lot more info about it here. In addition to a worthy and measurable target of program development and research investigating the efficacy and effectiveness of public mental health interventions, together, these findings suggest that perceived MHSE might be an important factor in overcoming mild to moderate mental health problems. Anyways, mental health ‘selfefficacy’ influences symptom outcomes of a self guided mobile phone and webbased psychotherapeutic intervention and may itself be a worthwhile target to increase the effectiveness and efficiency of online treatment programs.
With high construct validity, data from both Studies I and I provide support for the MHSES as a parsimonious and reliable measure of MHSE.
Factor analysis showed that the Scale is best considered unidimensional -the high internal consistency estimate providing further evidence that scale items function well gether to consistently measure MHSE.
Harrison et al. While coping skills and perceived control, including face to face therapies, further testing of the measure in other mental health interventions like generalised selfefficacy. While at identical time indicating that the scale measures a discrete construct, moderate correlations in the expected direction with measures of depressive symptoms. Work and social functioning and emotional stability support the construct validity of the MHSES. MHSES scores to change, a finding consistent with Bandura’s proposition that selfefficacy is a malleable psychological state, as opposed to a more permanent personality trait. Together, the available data provide preliminary endorsement for the MHSES as a psychometrically sound and easily administered measure of MHSE. For instance, while conforming to Bandura, a putative contributor to therapeutic outcomes in psychological interventions is perceived selfefficacy, and that’s, the degree to which an individual believes that she can perform a specific behaviour or set of behaviours.
Findings show that higher levels of ‘pretreatment’ self efficacy and increased selfefficacy over the course of treatment are important predictors of therapeutic success, and suggest that precise targeting of selfefficacy antecedent processes and information cues may assist in honing treatment efficiency and efficacy.
While reducing alcohol and drug use, weight removal, and chronic disease selfmanagement, -, in support of Bandura, ‘self efficacy’ is identified as a key factor explaining treatment gains and behavioural change in a couple of studies of health promoting behaviours, including smoking cessation.
Potential framework for understanding the effects of online interventions for mental health problems is provided by Bandura’s Social Learning Theory, a theory that specifies multiple interacting determinants of behaviour and behaviour change. Statistical analyses were completed with SPSS 21 dot 0 software.
Internal consistency reliability of the MHSES was assessed using Cronbach’s alpha, and construct validity was determined using Pearson’s correlation to relate baseline scores on the MHSES to theoretically related constructs,, including baseline measures of symptoms and overall psychological distress, work and social adjustment and neuroticism, a fact of personality that comprises a lack of emotional stability and confidence.
Maximum likelihood factor analysis with varimax rotation was used to examine the dimensionality of the MHSES and determine the final composition of the Scale, as our sample exceeded the widely accepted ratio of at least five subjects per variable.
Descriptive statistics were calculated for the DASS, WSAS and TIPI. Recommendations for the optimal subjectstovariables ratio in factor analytic studies vary considerably. Fact, statistical analyses were completed with SPSS 21 software. Nonetheless, in the first instance, we used baseline data to ‘re examine’ the psychometric properties of the MHSES using similar procedures to those conducted in Study on the basis of the results of the exploratory FA, confirmatory factor analysis was conducted for the MHSES to further study its construct validity.
In Study I, use of the mobile phone and ‘webbased’ intervention was associated with increased MHSE, and MHSE was linked with reduced depression, anxiety and stress symptoms, and improved work and social functioning.
With improvements in MHSE associated with the greatest symptom gains, importantly, we also found evidence for a potential mediating effect of MHSE on anxiety and stress symptoms.
These findings are in line with studies showing the benefits for health behaviours and physical health outcomes of interventions that enhance ‘selfefficacy’ -, gether and webbased therapies. Consequently, data also identified MHSE as a potential moderator of treatment outcomes in the mobile phone and web based intervention. Skills, motivation, and self assurance necessary to better manage their mental health symptoms, Alternatively, given that individuals with low self efficacy typically lack confidence and require more guidance in managing activities, a self efficacy enhancing web based intervention may provide exactly what they need. Interestingly, while Bandura’s SLT posits greater therapeutic gain for people with high ‘pretreatment’ MHSE, we found that users of the intervention with low MHSE typically reported the greatest symptom improvement. One possibility is that gains were greatest for low selfefficacy for a while being that their higher symptom scores at baseline left them with greater potential for improvement.
