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A Study Protocol for Testing the Effectiveness of User-Generated Content in Reducing Excessive Consumption.

ABSTRACT: Excessive consumption is on the rise, as is apparent in growing financial debt and global greenhouse gas emissions. Voluntary simplicity, a lifestyle choice of reduced consumption and sustainable consumer behavior, provides a potential solution for excessive consumers. However, voluntary simplicity is unpopular, difficult to adopt, and under researched. The outlined research project will test a method of promoting voluntary simplicity via user-generated content, thus mimicking an existing social media trend (Minimalism) in an empirical research design. The project will test (a) whether the Minimalism trend could benefit consumers interested in reducing their consumption, and (b) whether self-transcendence (i.e., biospheric) and self-enhancement (i.e., egoistic and hedonic) values and goals have a similar impact in promoting voluntary simplicity. A one-week intervention program will test the efficacy of watching user-generated voluntary simplicity videos in reducing non-essential consumption. Each of the two intervention conditions will present participants with similar tutorial videos on consumption reduction (e.g., decluttering, donating), while priming the relevant values and goals (self-transcendence or self-enhancement). These interventions will be compared to a control condition, involving no user-generated content. Participants will undergo baseline and post-intervention evaluations of: voluntary simplicity attitudes and behaviors, buying and shopping behaviors, values and goals in reducing consumption, and life satisfaction. Experience sampling will monitor affective state during the intervention. We provide a detailed stepwise procedure, materials, and equipment necessary for executing this intervention. The outlined research design is expected to contribute to the limited literature on voluntary simplicity, online behavioral change interventions, and the use of social marketing principles in consumer interventions.

SUBMITTER: Herziger A

PROVIDER: S-EPMC5465384 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A Study Protocol for Testing the Effectiveness of User-Generated Content in Reducing Excessive Consumption.

Herziger Atar A Benzerga Amel A Berkessel Jana J Dinartika Niken L NL Franklin Matija M Steinnes Kamilla K KK Sundström Felicia F

Frontiers in psychology 20170609

Excessive consumption is on the rise, as is apparent in growing financial debt and global greenhouse gas emissions. Voluntary simplicity, a lifestyle choice of reduced consumption and sustainable consumer behavior, provides a potential solution for excessive consumers. However, voluntary simplicity is unpopular, difficult to adopt, and under researched. The outlined research project will test a method of promoting voluntary simplicity via user-generated content, thus mimicking an existing social ...[more]

PMID: 28649220

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Project description:BackgroundOnline health communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters globally. Chinese OHCs are no exception. However, user-generated content (UGC) and the associated user behaviors in Chinese OHCs are largely underexplored and rarely analyzed systematically, forfeiting valuable opportunities for optimizing treatment design and care delivery with insights gained from OHCs.ObjectiveThis study aimed to reveal both the shared and distinct characteristics of 2 popular OHCs in China by systematically and comprehensively analyzing their UGC and the associated user behaviors.MethodsWe concentrated on studying the lung cancer forum (LCF) and breast cancer forum (BCF) on Mijian, and the diabetes consultation forum (DCF) on Sweet Home, because of the importance of the 3 diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explored the key user activities, small-world effect, and scale-free characteristics of each social network. We examined the UGC of these forums comprehensively and adopted the weighted knowledge network technique to discover salient topics and latent relations among these topics on each forum. Finally, we discussed the public health implications of our analysis findings.ResultsOur analysis showed that the number of reads per thread on each forum followed gamma distribution (HL=0, HB=0, and HD=0); the number of replies on each forum followed exponential distribution (adjusted RL2=0.946, adjusted RB2=0.958, and adjusted RD2=0.971); and the number of threads a user is involved with (adjusted RL2=0.978, adjusted RB2=0.964, and adjusted RD2=0.970), the number of followers of a user (adjusted RL2=0.989, adjusted RB2=0.962, and adjusted RD2=0.990), and a user's degrees (adjusted RL2=0.997, adjusted RB2=0.994, and adjusted RD2=0.968) all followed power-law distribution. The study further revealed that users are generally more active during weekdays, as commonly witnessed in all 3 forums. In particular, the LCF and DCF exhibited high temporal similarity (ρ=0.927; P<.001) in terms of the relative thread posting frequencies during each hour of the day. Besides, the study showed that all 3 forums exhibited the small-world effect (mean σL=517.15, mean σB=275.23, and mean σD=525.18) and scale-free characteristics, while the global clustering coefficients were lower than those of counterpart international OHCs. The study also discovered several hot topics commonly shared among the 3 disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study found that after the outbreak of COVID-19, users on the LCF and BCF were much more likely to bring up COVID-19-related issues while discussing their medical issues.ConclusionsUGC and related online user behaviors in Chinese OHCs can be leveraged as important sources of information to gain insights regarding individual and population health conditions. Effective and timely mining and utilization of such content can continuously provide valuable firsthand clues for enhancing the situational awareness of health providers and policymakers.

Project description:Introduction:User generated content (UGC) is a valuable but underutilized source of information about individuals who participate in online cessation interventions. This study represents a first effort to passively detect smoking status among members of an online cessation program using UGC. Methods:Secondary data analysis was performed on data from 826 participants in a web-based smoking cessation randomized trial that included an online community. Domain experts from the online community reviewed each post and comment written by participants and attempted to infer the author's smoking status at the time it was written. Inferences from UGC were validated by comparison with self-reported 30-day point prevalence abstinence (PPA). Following validation, the impact of this method was evaluated across all individuals and time points in the study period. Results:Of the 826 participants in the analytic sample, 719 had written at least one post from which content inference was possible. Among participants for whom unambiguous smoking status was inferred during the 30 days preceding their 3-month follow-up survey, concordance with self-report was almost perfect (kappa = 0.94). Posts indicating abstinence tended to be written shortly after enrollment (median = 14 days). Conclusions:Passive inference of smoking status from UGC in online cessation communities is possible and highly reliable for smokers who actively produce content. These results lay the groundwork for further development of observational research tools and intervention innovations. Implications:A proof-of-concept methodology for inferring smoking status from user generated content in online cessation communities is presented and validated. Content inference of smoking status makes a key cessation variable available for use in observational designs. This method provides a powerful tool for researchers interested in online cessation interventions and establishes a foundation for larger scale application via machine learning.

Project description:BackgroundRecent research has investigated the utility of mobile phone-delivered interventions for reducing risky single-occasion drinking, also known as binge drinking. In the past five years, focus has been placed on ecological momentary interventions (EMIs), which aim to deliver intervention content in correspondence to real-time assessments of behavior, also known as ecological momentary assessments (EMAs).ObjectiveThis study aims to assess the effect of a fully automated, tailored, mobile phone-delivered EMI termed Mobile Intervention for Drinking in Young people (MIDY) on young people's risky single-occasion drinking behavior.MethodsWe will use a three-armed randomized controlled trial design to determine the impact of MIDY on peak consumption of alcohol among young people. A list of mobile telephone numbers for random digit dialing will be generated, and researchers will telephone potential participants to screen for eligibility. Participants will be randomized into one of three intervention groups. For 6 weeks, EMI, EMA, and attention control groups will complete hourly EMA surveys on their mobile phones on Friday and Saturday nights. EMI participants will receive personalized feedback in the form of text messages corresponding to their EMA survey responses, which focus on alcohol consumption, spending, and mood. EMA participants will not receive feedback. A third group will also complete EMA and receive feedback text messages at the same time intervals, but these will be focused on sedentary behavior and technology use. All groups will also complete a short survey on Saturday and Sunday mornings, with the primary outcome measure taken on Sunday mornings. A more detailed survey will be sent on the final Sunday of the 6-week period, and then again 1 year after recruitment.ResultsThe primary outcome measure will be an observed change (ie, reduction) in the mean peak number of drinks consumed in a single night over the 6-week intervention period between the EMI and attention control groups as measured in the weekly EMA. We expect to see a greater reduction in mean peak drinking in the EMI group compared to that in the attention control group. As a secondary aim, we will assess whether mean peak drinking is reduced in the EMA group compared to the attention control group. We will use a random-effects mixed-modeling approach using maximum-likelihood estimation to provide estimates of differences in peak drinking across time periods between those receiving the intervention (EMI) and attention control participants. An intention-to-treat approach will be taken for the analysis. Individuals and study groups will be modeled as random and fixed factors, respectively.ConclusionsThis study extends our previous work investigating the efficacy of a mobile EMI (MIDY) for reducing risky drinking among young adults in Australia, and will add to the expanding literature on the use of mobile interventions for reducing risky alcohol consumption.Trial registrationAustralian New Zealand Clinical Trials Registration (ANZCTR): ACTRN12617001509358p; http://www.anzctr.org.au/ACTRN12617001509358p.aspx.International registered report identifier (irrid)DERR1-10.2196/14190.

Project description:BACKGROUND:Patient narrative data in online health care forums (communities) are receiving increasing attention from the scientific community for implementing patient-centered care. Natural language processing (NLP) methods are gaining more and more attention because of the enormous data volume. However, state-of-the-art NLP still cannot meet the need of high-resolution analysis of patients' narratives. Manual qualitative analysis still plays a pivotal role in answering complicated research questions from analyzing patient narratives. OBJECTIVE:This study aimed to develop a systematic framework for qualitative analysis of patient-generated narratives in online health care forums. METHODS:Our systematic framework consists of 4 phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results. Data collection and data preparation phases are constructed based on text mining methods for identifying appropriate online health forums for data collection, differentiating posts of patients from other stakeholders, protecting patients' privacy, sampling, and choosing the unit of analysis. Content analysis phase is built on the framework method, which facilitates and accelerates the identification of patterns and themes by an interdisciplinary research team. In the end, the focus of interpretation of the results phase is to measure the data quality and interpret the findings regarding the dimensions and aspects of patients' experiences and concerns in their original contexts. RESULTS:We demonstrated the usability of the proposed systematic framework using 2 case studies: one on determining factors affecting patients' attitudes toward antidepressants and another on identifying the disease management strategies in patient with diabetes facing financial difficulties. The framework provides a clear step-by-step process for systematic content analysis of patient narratives and produces high-quality structured results that can be used for describing patterns or regularities in patients' experiences, generating and testing hypotheses, and identifying areas of improvement in the health care systems. CONCLUSIONS:The systematic framework is a rigorous and standardized method for qualitative analysis of patient narratives. Findings obtained through such a process indicate authentic dimensions and aspects of patient experiences and shed light on patients' concerns, needs, preferences, and values, which are the core of patient-centered care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):RR1-10.2196/13914.

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A Study Protocol for Testing the Effectiveness of User-Generated Content in Reducing Excessive Consumption.

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A Study Protocol for Testing the Effectiveness of User-Generated Content in Reducing Excessive Consumption.

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