scholarly journals Determining Acceptance of e-mental Health Interventions in Digital Psychodiabetology: Using the Unified Theory of Acceptance and Use of Technology (Preprint)

2021 ◽  
Author(s):  
Mirjam Damerau ◽  
Martin Teufel ◽  
Venja Musche ◽  
Hannah Kohler ◽  
Adam Schweda ◽  
...  
Keyword(s):  
Mental Health ◽  
Regression Model ◽  
Health Interventions ◽  
Diabetic Patients ◽  
Unified Theory ◽  
Use Of Technology ◽  
Significant Difference ◽  
Mental Health Interventions ◽  
Explained Variance ◽  
Diabetes Patients

BACKGROUND Diabetes is a very common chronic disease, which confronts patients with massive physiological and psychological burdens. The digitalization of mental health care has generated effective e-mental health approaches, which bear indubitable practical value to patient treatment. However, before implementing and optimizing e-mental health tools, their acceptance and underlying barriers and resources should be determined first in order to be able to develop and establish effective patient-oriented interventions. OBJECTIVE This study aimed to assess the acceptance of e-mental health interventions in diabetes patients and to explore its underlying barriers and resources. METHODS A cross-sectional study was conducted in Germany over a period of two months in 2020 through an online survey recruited via online diabetes channels. Eligibility requirement was adult age (18 or above), a good command of the German language, internet access and a diagnosis of diabetes. Acceptance was measured using a modified questionnaire, which was based on the well-established Unified Theory of Acceptance and Use of Technology (UTAUT) and assessed health-related internet use, acceptance of e-mental health interventions and its barriers and resources. Mental health was measured using validated and established instruments, namely the Generalized Anxiety Disorder Scale-7, the Patient Health Questionnaire-2 and the Distress Thermometer. Additionally, socio-demographic and medical data regarding diabetes were asked RESULTS Of 340 participants starting the survey 76.8 % completed it, resulting in 261 participants and a final sample of 258 participants with complete datasets. The acceptance of e-mental health interventions in diabetes patients was overall moderate (M = 3.02, SD = 1.14). Sex and suffering from a mental disorder had a significant influence on acceptance (P < .001). In an extended UTAUT regression model (UTAUT predictors plus socio-demographics and mental health variables) acceptance was significantly predicted by distress (β = .11, P = .027) as well as by the UTAUT predictors performance expectancy (PE) (β = .50, P < .001), effort expectancy (EE) (β = .15, P = .001), and social influence (SI) (β = .28, P < .001). The comparison between an extended UTAUT regression model (13 predictors) and the UTAUT only regression model (PE, EE, SI) revealed no significant difference in explained variance (F10,244 = 1.567, P =.117). CONCLUSIONS This study supports the viability of the UTAUT model and its predictors in assessing acceptance of e-mental health interventions in diabetes patients. Three UTAUT predictors reached a notable amount of explained variance in acceptance of 75 %, indicating being a very useful and efficient method for measuring e-mental health intervention acceptance of diabetic patients. Due to the close link between acceptance and utilization, acceptance facilitating interventions focusing on these three UTAUT predictors should be fostered to bring forward the highly needed establishment of effective e-mental health interventions in psychodiabetology.

Predicting Acceptance of e-Mental Health Interventions in Patients with Obesity by using an extended Unified Theory of Acceptance Model (Preprint)

2021 ◽  
Author(s):  
Vanessa Rentrop ◽  
Mirjam Damerau ◽  
Adam Schweda ◽  
Jasmin Steinbach ◽  
Lynik Chantal Schüren ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Interventions ◽  
Unified Theory ◽  
Obese Patients ◽  
Utaut Model ◽  
Significant Difference ◽  
Mental Health Interventions ◽  
Explained Variance ◽  
Health Burdens ◽  
The Impact

BACKGROUND The rapid increase in the number of overweight and obese people is a worldwide health problem. Obesity is often associated with physiological and mental health burdens. Due to several barriers of face-to-face psychotherapy, one promising approach is to exploit recent developments and implement innovative e-mental health interventions that offer various benefits to obese patients as well as for the healthcare system. OBJECTIVE This study aimed to assess the acceptance of e-mental health interventions in patients with obesity and explore its influencing predictors. In addition, the well-established, Unified Theory of Acceptance and Use of Technology model (UTAUT) will be compared with an extended UTAUT model in terms of variance explanation of acceptance. METHODS A cross-sectional online survey study was conducted from July 2020 to January 2021 in Germany. Eligibility requirement was adult age (18 or above), internet access, a good command of the German language, and a BMI > 30 kg/m2 (obesity). 448 patients with obesity (grade I, II and III) were recruited via specialized social media platforms. The impact of various socio-demographic, medical, and mental health characteristics were assessed. eHealth-related data and acceptance of e-mental health interventions were examined using a modified questionnaire, which is based on the UTAUT. RESULTS Acceptance of e-mental health interventions in obese patients was overall moderate (M = 3.18, SD = 1.11). There are significant differences in acceptance of e-mental health interventions among obese patients depending on the degree of obesity, age, gender, occupational status, and mental health status. In an extended UTAUT regression model acceptance was significantly predicted by the depression score (PHQ-8) (β = .07, P = .028), stress due to constant availability via mobile phone or email (β = .06, P = .024) and the confidence in using digital media (β = -.058, P = .042), as well as by the UTAUT core predictors performance expectancy (PE) (β = .45, P < .001), effort expectancy (EE) (β = .22, P < .001), and social influence (SI) (β = .27, P < .001). The comparison between an extended UTAUT model (16 predictors) and the restrictive UTAUT model (PE, EE, SI) revealed a significant difference in explained variance (F13,431= 2.366, P = .005). CONCLUSIONS The UTAUT model has proven to be a valuable instrument to predict the acceptance of e-mental health interventions in patients with obesity. Furthermore, when additional predictors were added, a significantly higher percentage of explained variance in acceptance could be achieved. Based on the strong association between acceptance and future utilization, new interventions should focus on these UTAUT predictors to promote the urgently needed establishment of effective e-mental health interventions for patients with obesity, who suffer from mental health burdens.

Adolescent Dropout from Brief Digital Mental Health Interventions Within and Beyond Randomized Trials

2021 ◽  
Author(s):  
Katherine Cohen ◽  
Jessica L. Schleider
Keyword(s):  
Mental Health ◽  
Program Evaluation ◽  
Controlled Trial ◽  
Health Interventions ◽  
Completion Rates ◽  
Demographic Groups ◽  
Completion Status ◽  
Significant Difference ◽  
Mental Health Interventions ◽  
Time Required

Objective: Many adolescents struggle to access appropriate mental health care due to structural or psychological barriers. Among those who do access an intervention, retention is a pressing concern. As a result, adolescents are less likely to benefit from an intervention. Although traditional barriers to participation (e.g., location, cost) are hypothetically reduced or removed in internet interventions, low retention is still common, particularly in unguided programs (those not involving a clinician). It is therefore key to determine what factors are associated with dropout in digital mental health interventions with adolescents both within and beyond the context of research studies. Methods: We compare completion rates from two projects evaluating self-guided, online single-session mental health interventions (SSIs) for adolescents. One was a randomized controlled trial (RCT) in which participants were paid for participation. The other was a program evaluation project in which participants were not paid for participation. We additionally compare SSI completion rates across various demographic groups and across baseline hopelessness levels. Results: There was a statistically significant difference in SSI completion status between the RCT (84.75% full-completers) and the program evaluation (36.86% full-completers), X2 (2, N =2436) = 583.5, p &lt; .05. There were no significant differences in the baseline hopelessness scores across completion statuses in either study. There were no significant differences in full-completion rates across demographic groups in either project. Conclusion: Adolescents may be more likely to complete a brief digital mental health intervention if they are paid for participation. Additionally, it is possible that the brevity of SSIs reduces demographic disparities related to retention by minimizing the time required to complete an intervention.

scholarly journals Effectiveness of Mental Health Intervention for Suicide Prevention

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Nimesh G. Desai ◽  
Vishi Sachdeva ◽  
Aishwarya John ◽  
Kumar Gourav ◽  
Gibson O. Anugwom
Keyword(s):  
Mental Health ◽  
Family Members ◽  
Health Intervention ◽  
Health Interventions ◽  
P Value ◽  
Mental Health Intervention ◽  
Suicide Behavior ◽  
Significant Difference ◽  
Before And After ◽  
Mental Health Interventions

Background: Various mental health interventions like priority in-patient care, ECT, psychotherapies, pharmacotherapies, etc. have been tried throughout the world to decrease the morbidity and mortality associated with suicide behavior. Aims: To establish the effectiveness of mental health intervention for preventing suicide, for those at risk and to understand the perception of patients and family members about the usefulness of interventions for preventing suicide. Material and methods: The patients admitted to the Psychiatry Intensive Care Unit (PICU) at the Institute of Human Behavior and Allied Sciences (IHBAS), in view of suicide behavior, during the 12 months period from 1st July 2018 to 30th June 2019 were included in the study. A target population of 88 patients was taken up for cross-sectional follow-up assessment. They were assessed for suicide behavior for the period of 12 months prior to and subsequent to the hospitalization. Results: A statistically significant difference was found in both, the number of patients attempting suicide before and after hospitalization (N = 88, Chi-square = .2, p-value < 0.04), as well as in the mean number of attempts before and after hospitalization (N = 88, p-value <0.01). Also, three fourth of patients/family members were completely satisfied with the care provided while the remaining one-fourth were only partially satisfied. Conclusion: This study has established not only the usefulness of timely mental health intervention for the prevention of suicide as perceived by family or patients but also provides statistical evidence for the effectiveness of such mental health interventions.

Review of Mental Health Interventions for the Aging.

1982 ◽  
Vol 27 (9) ◽  
pp. 742-743
Author(s):  
Richard Schulz
Keyword(s):  
Mental Health ◽  
Health Interventions ◽  
Mental Health Interventions
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