Preparation and characterization of the ‘research chemical’ diphenidine,its pyrrolidine analogue,and their 2,2‐diphenylethyl isomers

Substances with the diphenylethylamine nucleus represent a recent addition to the product catalog of dissociative agents sold as ‘research chemicals’ on the Internet. Diphenidine, i.e. 1‐(1,2‐diphenylethyl)piperidine (1,2‐DEP), is such an example but detailed analytical data are less abundant. The present study describes the synthesis of diphenidine and its most obvious isomer, 1‐(2,2‐diphenylethyl)piperidine (2,2‐DEP), in order to assess the ability to differentiate between them. Preparation and characterization were also extended to the two corresponding pyrrolidine analogues 1‐(1,2‐diphenylethyl)‐ and 1‐(2,2‐diphenylethyl)pyrrolidine, respectively. Analytical characterizations included high‐resolution electrospray mass spectrometry (HR‐ESI‐MS), liquid chromatography ESI‐MS/MS, gas chromatography ion trap electron and chemical ionization MS, nuclear magnetic resonance spectroscopy (NMR) and infrared spectroscopy. Differentiation between the two isomeric pairs was possible under GC‐(EI/CI)‐MS conditions and included the formation of distinct iminium ions, such as m/z 174 for 1,2‐DEP and m/z 98 for 2,2‐DEP, respectively. The pyrrolidine counterparts demonstrated similar phenomena including the expected mass difference of 14 Da due to the lack of one methylene unit in the ring. Two samples obtained from an Internet vendor provided confirmation that diphenidine was present in both samples, concurring with the product label. Finally, it was confirmed that diphenidine (30 μM) reduced N‐methyl‐D ‐aspartate‐mediated field excitatory postsynaptic potentials (NMDA‐fEPSPs) to a similar extent to that of ketamine (30 μM) when using rat hippocampal slices. The appearance of 1,2‐ diphenylethylamines appears to reflect the exploration of alternatives to arylcyclohexylamine‐type substances, such as methoxetamine, PCP and PCPy‐based analogues that also show NMDA receptor activity as demonstrated here for diphenidine. Copyright © 2014 John Wiley & Sons, Ltd.     

Transdiagnostic versus disorder-specific and clinician-guided versus self-guided internet-delivered treatment for Social Anxiety Disorder and comorbid disorders: A randomized controlled trial

Disorder-specific (DS-CBT) and transdiagnostic (TD-CBT) cognitive behaviour therapy have both been used to treat social anxiety disorder (SAD). This study compared internet-delivered DS-CBT and TD-CBT for SAD across clinician-guided (CG-CBT) and self-guided (SG-CBT) formats. Participants with SAD (n = 233) were randomly allocated to receive internet-delivered TD-CBT or DS-CBT and CG-CBT or SG-CBT. Large reductions in symptoms of SAD (Cohen’s d ≥ 1.01; avg. reduction ≥ 30%) and moderate-to-large reductions in symptoms of comorbid depression (Cohen’s d ≥ 1.25; avg. reduction ≥ 39%), generalised anxiety disorder (Cohen’s d ≥ 0.86; avg. reduction ≥ 36%) and panic disorder (Cohen’s d ≥ 0.53; avg. reduction ≥ 25%) were found immediately post-treatment and were maintained or further improved to 24-month follow-up. No marked differences were observed between TD-CBT and DS-CBT or CG-CBT and SG-CBT highlighting the potential of each for the treatment of SAD and comorbid disorders.     

Characterizing the Processes for Navigating Internet Health Information Using Real-Time Observations: A Mixed-Methods Approach

BackgroundLittle is known about the processes people use to find health-related information on the Internet or the individual characteristics that shape selection of information-seeking approaches.ObjectiveOur aim was to describe the processes by which users navigate the Internet for information about a hypothetical acute illness and to identify individual characteristics predictive of their information-seeking strategies.MethodsStudy participants were recruited from public settings and agencies. Interested individuals were screened for eligibility using an online questionnaire. Participants listened to one of two clinical scenarios—consistent with influenza or bacterial meningitis—and then conducted an Internet search. Screen-capture video software captured Internet search mouse clicks and keystrokes. Each step of the search was coded as hypothesis testing (etiology), evidence gathering (symptoms), or action/treatment seeking (behavior). The coded steps were used to form a step-by-step pattern of each participant’s information-seeking process. A total of 78 Internet health information seekers ranging from 21-35 years of age and who experienced barriers to accessing health care services participated.ResultsWe identified 27 unique patterns of information seeking, which were grouped into four overarching classifications based on the number of steps taken during the search, whether a pattern consisted of developing a hypothesis and exploring symptoms before ending the search or searching an action/treatment, and whether a pattern ended with action/treatment seeking. Applying dual-processing theory, we categorized the four overarching pattern classifications as either System 1 (41%, 32/78), unconscious, rapid, automatic, and high capacity processing; or System 2 (59%, 46/78), conscious, slow, and deliberative processing. Using multivariate regression, we found that System 2 processing was associated with higher education and younger age.ConclusionsWe identified and classified two approaches to processing Internet health information. System 2 processing, a methodical approach, most resembles the strategies for information processing that have been found in other studies to be associated with higher-quality decisions. We conclude that the quality of Internet health-information seeking could be improved through consumer education on methodical Internet navigation strategies and the incorporation of decision aids into health information websites.     

Integrating Health Belief Model and Technology Acceptance Model: An Investigation of Health-Related Internet Use

Background

Today, people use the Internet to satisfy health-related information and communication needs. In Malaysia, Internet use for health management has become increasingly significant due to the increase in the incidence of chronic diseases, in particular among urban women and their desire to stay healthy. Past studies adopted the Technology Acceptance Model (TAM) and Health Belief Model (HBM) independently to explain Internet use for health-related purposes. Although both the TAM and HBM have their own merits, independently they lack the ability to explain the cognition and the related mechanism in which individuals use the Internet for health purposes.

Objective

This study aimed to examine the influence of perceived health risk and health consciousness on health-related Internet use based on the HBM. Drawing on the TAM, it also tested the mediating effects of perceived usefulness of the Internet for health information and attitude toward Internet use for health purposes for the relationship between health-related factors, namely perceived health risk and health consciousness on health-related Internet use.

Methods

Data obtained for the current study were collected using purposive sampling; the sample consisted of women in Malaysia who had Internet access. The partial least squares structural equation modeling method was used to test the research hypotheses developed.

Results

Perceived health risk (β=.135, t ₁₉₉₉=2.676) and health consciousness (β=.447, t ₁₉₉₉=9.168) had a positive influence on health-related Internet use. Moreover, perceived usefulness of the Internet and attitude toward Internet use for health-related purposes partially mediated the influence of health consciousness on health-related Internet use (β=.025, t ₁₉₉₉=3.234), whereas the effect of perceived health risk on health-related Internet use was fully mediated by perceived usefulness of the Internet and attitude (β=.029, t ₁₉₉₉=3.609). These results suggest the central role of perceived usefulness of the Internet and attitude toward Internet use for health purposes for women who were health conscious and who perceived their health to be at risk.

Conclusions

The integrated model proposed and tested in this study shows that the HBM, when combined with the TAM, is able to predict Internet use for health purposes. For women who subjectively evaluate their health as vulnerable to diseases and are concerned about their health, cognition beliefs in and positive affective feelings about the Internet come into play in determining the use of health-related Internet use. Furthermore, this study shows that engaging in health-related Internet use is a proactive behavior rather than a reactive behavior, suggesting that TAM dimensions have a significant mediating role in Internet health management.     

E-Mental Health Care Among Young Adults and Help-Seeking Behaviors: A Transversal Study in a Community Sample

Background

The Internet is widely used by young people and could serve to improve insufficient access to mental health care. Previous information on this topic comes from selected samples (students or self-selected individuals) and is incomplete.

Objective

In a community sample of young adults, we aimed to describe frequency of e-mental health care study-associated factors and to determine if e-mental health care was associated with the use of conventional services for mental health care.

Methods

Using data from the 2011 wave of the TEMPO cohort study of French young adults (N=1214, aged 18-37 years), we examined e-mental health care and associated factors following Andersen’s behavioral model: predisposing factors (age, sex, educational attainment, professional activity, living with a partner, children, childhood negative events, chronic somatic disease, parental history of depression), enabling factors (social support, financial difficulties, parents’ income), and needs-related factors (lifetime major depression or anxiety disorders, suicidal ideation, ADHD, cannabis use). We compared traditional service use (seeking help from a general practitioner, a psychiatrist, a psychologist; antidepressant or anxiolytics/hypnotics use) between participants who used e-mental health care versus those who did not.

Results

Overall, 8.65% (105/1214) of participants reported seeking e-mental health care in case of psychological difficulties in the preceding 12 months and 15.7% (104/664) reported psychological difficulties. Controlling for all covariates, the likelihood of e-mental health care was positively associated with 2 needs-related factors, lifetime major depression or anxiety disorder (OR 2.36, 95% CI 1.36-4.09) and lifetime suicidal ideation (OR 1.91, 95% CI 1.40-2.60), and negatively associated with a predisposing factor: childhood life events (OR 0.60, 95% CI 0.38-0.93). E-mental health care did not hinder traditional care, but was associated with face-to-face psychotherapy (66.2%, 51/77 vs 52.4%, 186/355, P=.03).

Conclusions

E-mental health care represents an important form of help-seeking behavior for young adults. Professionals and policy makers should take note of this and aim to improve the quality of online information on mental health care and to use this fact in clinical care.     

A Web-Based Psychoeducational Program for Informal Caregivers of Patients With Alzheimer’s Disease: A Pilot Randomized Controlled Trial

Background

Although several face-to-face programs are dedicated to informal caregivers of persons with dementia, they are not always accessible to overburdened or isolated caregivers. Based on a face-to-face intervention program, we adapted and designed a Web-based fully automated psychoeducational program (called Diapason) inspired by a cognitive approach.

Objective

This study aimed to evaluate through a pilot unblinded randomized controlled trial the efficacy and acceptability of a Web-based psychoeducational program for informal caregivers of persons with Alzheimer’s disease (PWAD) based on a mixed methods research design.

Methods

We recruited and randomized offline 49 informal caregivers of a PWAD in a day care center in Paris, France. They either received the Web-based intervention and usual care for 3 months (experimental group, n=25) or only usual care (control group, n=24). Caregivers’ perceived stress (PSS-14, primary outcome), self-efficacy, burden, perceived health status, and depression (secondary outcomes) were measured during 3 face-to-face on-site visits: at baseline, at the end of the program (month 3), and after follow-up (month 6). Additionally, semistructured interviews were conducted with experimental group caregivers at month 6 and examined with thematic analysis.

Results

Intention-to-treat analysis did not show significant differences in self-perceived stress between the experimental and control groups (P=.98). The experimental group significantly improved their knowledge of the illness (d=.79, P=.008) from baseline to month 3. Of the 25 participants allocated to the experimental group, 17 (71%) finished the protocol and entirely viewed at least 10 of 12 online sessions. On average, participants used the website 19.72 times (SD 12.88) and were connected for 262.20 minutes (SD 270.74). The results of the satisfaction questionnaire showed that most participants considered the program to be useful (95%, 19/20), clear (100%, 20/20), and comprehensive (85%, 17/20). Significant correlations were found between relationship and caregivers’ program opinion (P=.01). Thus, positive opinions were provided by husbands and sons (3/3), whereas qualified opinions were primarily reported by daughters (8/11). Female spouses expressed negative (2/3) or neutral opinions (1/3). Caregivers expected more dynamic content and further interaction with staff and peers.

Conclusions

In this study, quantitative results were inconclusive owing to small sample size. Qualitative results indicated/showed little acceptance of the program and high expectations from caregivers. Caregivers did not rule out their interest in this kind of intervention provided that it met their needs. More dynamic, personalized, and social interventions are desirable. Our recruitment issues pointed out the necessity of in-depth studies about caregivers’ help-seeking behaviors and readiness factors.

Trial Registration

Clinicaltrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01430286","term_id":"NCT01430286"}}NCT01430286; http://clinicaltrials.gov/ct2/show/{"type":"clinical-trial","attrs":{"text":"NCT01430286","term_id":"NCT01430286"}}NCT01430286 (Archived by WebCite at http://www.webcitation/6KxHaRspL).