Digital Intervention for the Modification of Lifestyles (iGame)

Effectiveness of a Digital Intervention Based on Modification of Lifestyles in Secondary Prevention: iGAME Controlled Randomized Clinical Trial

The objective of the project is to analyze the clinical effectiveness of a gamifield mHealth application (iGAME) and developed in the context of lifestyle modification, but with the approach of the Behaviour Change Technique, through a randomized clinical trial that affects secondary prevention in three clinical subtypes of noncommunicable diseases, where lifestyle modification is the center of its best practice.

Despite digital exposure, gamification of health has been widely understood and often applied ad hoc in health products. Attempts to incorporate game concepts into digital health applications have not led to demonstrated success. Recent studies have shown that only 4% of the best rated health apps in Apple stores and Google Play (based on revenue and download) have gamification elements, but less than 5% of these health apps have been included in the application library of National Health Service. In addition, very little of 5% was developed for industry and health professionals. If the power of digital technologies, such as games for clear clinical benefits, is not released, opportunities for social and economic burial will be lost for all stakeholders in the digital health and digital economy ecosystem. A number of factors in this barrier: The best techniques for the design of activities. The majority of health gamification has little consistent support of health or clinical theories. The high cost and complexity of the digital game development process. The majority of gaming functions are based on best practices in the development of digital games. Little participation of researchers in health, professionals and participation of the end user in the process of gamification development. Very little health gamification is formally evaluated clinically. The initial hypothesis is that after 12 weeks of participation in the original iGAME application, participants will increase the quantity and distribution of energy consumption, through the estimation of results, data based on acceleration and questionnaires. automatic information In addition, it will also improve satisfaction and lifestyle, as well as the consumption of health services.

Two groups study. One group with intervention (app mobile program); second group as control. At the end of the intervention, the control group receives advice of demonstrated effectiveness in the intervention to comply with the ethical principles.

The assigned participants will receive an intervention based on gamification and the use of behavior change techniques to reduce sedentary lifestyle. Thus, a new mobile application will be used for 12 weeks that proposes to the user the realization of activities with the aim of reducing their sedentary behavior. The development of the application is based on previous analyzes that propose 6 clusters that encompass 33 factors that influence sedentary behavior. In this way, the application is designed to act on the two accessible: social support and behavior. On the social support, he proposes to the user to share his achievements in social networks or in an internal network of game users. In terms of habit modification, behavior modification strategies proposed in the Michie et al. (2013) taxonomy are applied, such as the following: establishment of personalized goals, rewards and reminders, awareness of achievements achieved, among others

The control group will receive the usual indications about the harms of sedentary lifestyle and the benefits of physical activity, not receiving specific intervention. In case the use of the intervention applied in the experimental group is beneficial, the participants assigned to the control group will be offered the opportunity to receive the intervention outside the study to allow the benefit to be used.

The information group will receive through a mobile application tips to reduce sedentary lifestyle and promote healthy living habits.

Patient reported outcome. It is an evaluation of sedentary behavior. An alternative way to the use of accelerometry for the calculation of energy consumption.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Patient reported outcome. Health index that relates quantity and quality of life. It is applied with a short questionnaire and a visual analogue scale. Each dimension is rated in five levels from 1 ("I have no problem with...") to 5 ("I am unable to..."). Each participant indicates the level that best reflects their state for each of the five dimensions, with which their health status is described by five digits that take values from 1 to 5, with health status 11111 being considered a priori the best state of health and 55555 the worst state of health. The visual analogue scale is scored from 0 (without pain) to 100 (worst pain).

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Patient reported outcome: tool designed to assess patient satisfaction with physiotherapy care through intrinsic and extrinsic factors. The instrument consists of 10 specific items and 2 global items scored from 1 (strongly disagree) to 5 (strongly agree). The means of items 1 through 3 and 4 through 10 are calculated to determine the mean score for external and internal subscales, respectively. Total score from 0 (worst patient satisfaction) to 5 (best patient satisfaction).

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Patient reported outcome:Questionnaire designed to evaluate cancer-related fatigue in breast cancer survivors. Composed of 22 numerically scaled, "0" to "10" items that measure four dimensions of subjective fatigue: behavioral/severity, affective meaning, sensory and cognitive/mood. To calculate the total fatigue score, add the 22-item scores together and divide by 22 in order to keep the score on the same numeric "0" to "10" scale. Severity codes: 0 none, 1-3 mild, 4-6 moderate, 7-10 severe.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Patient reported outcome: quantification of existing fear-avoidance components in patients with medical conditions associated with pain. 20 question related to painful medical condition. 5 = Completely Agree 4 = Mostly Agree 3 = Slightly Agree 2 = Slightly Disagree 1 = Mostly Disagree0 = Completely Disagree. Higher values represent a worse outcome.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

patient reported outcome. Assessment the degree of physical disability related to non-specific low back pain, understanding physical disability as limitation in the performance of activities of daily life.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Patient reported outcome. Assessment the presence and severity of depressive symptoms, relating to the last days of the previous week.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

Five measures will be carried out. 1st the beginning of the study. 2nd measurement after 1.5 months. 3rd measurement 3 months from the beginning. 4th measure 6 months from the beginning. 5th measure: 12 months from the begin.

IInclusion Criteria for Breast Cancer Survivors subgroup: Men and women Age between 18 and 65 years Sedentary behavior recognized by the subject: <1.5 METS per day and sitting> 4h / d . Intention to change sedentary behavior manifested by the subject Survivors of breast cancer. Women with a clinical history of diagnosis of primary breast cancer, having completed surgical treatment, radiotherapy or chemotherapy at least three months before starting the study intervention Inclusion Criteria for Low Back Pain subgroup: Men and women Age between 18 and 65 years Sedentary behavior recognized by the subject: <1.5 METS per day and sitting> 4h / d . Intention to change sedentary behavior manifested by the subject Mild low back pain of mechanical or degenerative cause diagnosed by a primary care physician Inclusion Criteria for Depression subgroup: Men and women Age between 18 and 65 years Sedentary behavior recognized by the subject: <1.5 METS per day and sitting> 4h / d . Intention to change sedentary behavior manifested by the subject Mild depression Diagnosis in Primary Care using the MINI interview to rule out another severe mental pathology and the PHQ-9 questionnaire to categorize the level of depressive severity Exclusion Criteria: Several mental illness Several illness that limits physical ability Phobia for digital technologies Difficulty in attending study measurements

The results emerging from this study are positive, negative or inconclusive with respect to the proposed hypothesis, these will be attempted to publish as scientific production in journals of high impact in the area of knowledge and indexed in Journal Citation Reports of ISI-Thompson, preferably of the 1-2th quartile. In addition, we will try to select Open Acess journals to favor the scientific dissemination of the results. In the same way, the results will be exposed in communications, papers, forums and discussion tables of different scientific and cultural days.

Edwards EA, Lumsden J, Rivas C, Steed L, Edwards LA, Thiyagarajan A, Sohanpal R, Caton H, Griffiths CJ, Munafo MR, Taylor S, Walton RT. Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps. BMJ Open. 2016 Oct 4;6(10):e012447. doi: 10.1136/bmjopen-2016-012447.

Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013 Aug;46(1):81-95. doi: 10.1007/s12160-013-9486-6.

Hoeppner BB, Hoeppner SS, Seaboyer L, Schick MR, Wu GW, Bergman BG, Kelly JF. How Smart are Smartphone Apps for Smoking Cessation? A Content Analysis. Nicotine Tob Res. 2016 May;18(5):1025-31. doi: 10.1093/ntr/ntv117. Epub 2015 Jun 4.

Wolf JA, Moreau JF, Akilov O, Patton T, English JC 3rd, Ho J, Ferris LK. Diagnostic inaccuracy of smartphone applications for melanoma detection. JAMA Dermatol. 2013 Apr;149(4):422-6. doi: 10.1001/jamadermatol.2013.2382.