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L., & Crusius, J. (2016). The interplay between Facebook use, social comparison, envy, and depression. Current Opinion in Psychology, 9, 44–49.\nBesser, A., & Priel, B. (2010). Grandiose narcissism versus vulnerable narcissism in threatening situations: emotional reactions to achievement failure and interpersonal rejection. Journal of Social and Clinical Psychology, 29(8), 874–902.\nBłachnio, A., Przepiorka, A., & Rudnicka, P. (2016). Narcissism and self-esteem as predictors of dimensions of Facebook use. Personality and Individual Differences, 90, 296–301.\nBlanton, H. (2001). Evaluating the self in the context of another: the three-selves model of social comparison assimilation and contrast. In G. Moskowitz (Ed.), Cognitive social psychology: the Princeton Symposium and the legacy and future of social cognition (pp. 75–88). Mahwah: Erlbaum.\nCasale, S., Fioravanti, G., & Rugai, L. (2016). Grandiose and vulnerable narcissists: who is at higher risk for social networking addiction? Cyberpsychology, Behavior and Social Networking, 19(8), 510–515.\nCNNIC. (2019). The 44th China statistical report on internet development. http:\u002F\u002Fwww.cnnic.net.cn\u002Fhlwfzyj\u002Fhlwxzbg\u002Fhlwtjbg\u002F201908\u002Ft20190830_70800.htm. Accessed 1 Mar 2020.\nCramer, P. (2011). Young adult narcissism: a 20 year longitudinal study of the contribution of parenting styles, preschool precursors of narcissism, and denial. Journal of Research in Personality, 45(1), 19–28.\nEşkisu, M., Hoşoğlu, R., & Rasmussen, K. (2017). An investigation of the relationship between Facebook usage, Big Five, self-esteem and narcissism. Computers in Human Behavior, 69, 294–301.\nHawk, S. T., van den Eijnden, R. J. J. M., Van Lissa, C. J., & Ter Bogt, T. F. M. (2018). Narcissistic adolescents’ attention-seeking following social rejection: links with social media disclosure, problematic social media use, and smartphone stress. Computers in Human Behavior, 92, 65–75.\nHayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis. Journal of Educational Measurement, 51(3), 335–337.\nHussain, Z., Griffiths, M. D., & Sheffield, D. (2017). An investigation into problematic smartphone use : the role of narcissism, anxiety, and personality factors. Journal of Behavioral Addictions, 6(3), 378–386.\nJohnson, B. K., & Knobloch-Westerwick, S. (2014). Glancing up or down: mood management and selective social comparisons on social networking sites. Computers in Human Behavior, 41, 33–39.\nKauten, R. L., Lui, J. H. L., Stary, A. K., & Barry, C. T. (2015). “Purging my friends list. Good luck making the cut”: perceptions of narcissism on Facebook. Computers in Human Behavior, 51, 244–254.\nKrizan, Z., & Bushman, B. J. (2011). Better than my loved ones: social comparison tendencies among narcissists. Personality and Individual Differences, 50(2), 212–216.\nKsinan, A. J., & Vazsonyi, A. T. (2016). Narcissism, internet, and social relations: a study of two tales. Personality and Individual Differences, 94, 118–123.\nLee, B. W., & Stapinski, L. A. (2012). Seeking safety on the internet: relationship between social anxiety and problematic internet use. Journal of Anxiety Disorders, 26(1), 197–205.\nLee, S. Y. (2014). How do people compare themselves with others on social network sites? The case of Facebook. Computers in Human Behavior, 32, 253–260.\nMiller, J. D., Hoffman, B. J., Gaughan, E. T., Gentile, B., Maples, J., & Campbell, W. K. (2011). Grandiose and vulnerable narcissism: a nomological network analysis. Journal of Personality, 79(5), 1013–1042.\nMorf, C. C., & Rhodewalt, F. (2001). Unraveling the paradoxes of narcissism: a dynamic self-regulatory processing model. Psychlogical Inquiry, 12(4), 177–196.\nNiu, G. F., Sun, X. J., Zhou, Z. K., Tian, Y., Liu, Q. Q., Lian, S. L. (2016). The effect of adolescents’ social networking site use on self-concept clarity: the mediating role of social comparison. Psychological Science, 39(1), 97–102. https:\u002F\u002Fwww.cnki.net\u002Fkcms\u002Fdoi\u002F10.16719\u002Fj.cnki.1671-6981.20160115.html\nOzimek, P., Bierhoff, H., & Hanke, S. (2018). Do vulnerable narcissists profit more from Facebook use than grandiose narcissists? An examination of narcissistic Facebook use in the light of self-regulation and social comparison theory. Personality and Individual Differences, 124, 168–177.\nOzimek, P., Baer, F., & Förster, J. (2017). Materialists on Facebook: the self-regulatory role of social comparisons and the objectification of Facebook friends. Heliyon, 3(11), e449.\nRose, P. (2002). The happy and unhappy faces of narcissism. Personality and Individual Differences, 33(3), 379–391.\nSapacz, M., Rockman, G., & Clark, J. (2016). Are we addicted to our cell phones? Computers in Human Behavior, 57, 153–159.\nSedikides, C., Rudich, E. A., Gregg, A. P., Kumashiro, M., & Rusbult, C. (2004). Are normal narcissists psychologically healthy? Self-esteem matters. Journal of Personality and Social Psychology, 87(3), 400–416.\nVander, Z. K., Oldersma, F. L., Buunk, B., & Bos, D. (1998). Social comparison preferences among cancer patients as related to neuroticism and social comparison orientation. Journal of Personality and Social Psychology, 75(3), 801–810.\nVogel, E. A., Rose, J. P., Okdie, B. M., Eckles, K., & Franz, B. (2015). Who compares and despairs? The effect of social comparison orientation on social media use and its outcomes. Personality and Individual Differences, 86, 249–256.\nWalther, J. B. (1996). Computer-mediated communication impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23(1), 3–43.\nWang, D. (2017). A study of the relationship between narcissism, extraversion, drive for entertainment, and narcissistic behavior on social networking sites. Computers in Human Behavior, 66, 138–148.\nWang, M., Wang, L., & Shi, J. (2006). Reliability and validation of the social comparison orientation scale. Chinese Mental Health Journal, 5, 302–305 CNKI:SUN:ZXWS.0.2006-05-008.\nWang, X. (2008). Research on the influence of college students’ narcissistic personality on self-esteem and subjective well-being. Shanxi Normal University, Master thesis.\nWink, P. (1991). Two faces of narcissism. Journal of Personality and Social Psychology, 61(4), 590–597.\nXing, S., & Yu, G. (2006). Social comparison: contrast effect or assimilation effect?. Advances in. Psychological Science, 14(6), 944–949. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1671-3710.2006.06.023.\nXiong, J., Zhou, Z., Chen, W., You, Z., & Zhai, Z. (2012). Development of the mobile phone addiction tendency scale for college students. Chinese Mental Health Journal, 26(3), 222–225 CNKI:SUN:ZXWS.0.2012-03-017.\nYen, C., Tang, T., Yen, J., Lin, H., Huang, C., Liu, S., & Ko, C. (2009). Symptoms of problematic cellular phone use, functional impairment and its association with depression among adolescents in southern Taiwan. Journal of Adolescence, 32(4), 863–873.\nZheng, Y., & Huang, L. (2005). Overt and covert narcissism: a psychological exploration of narcissistic personality. Psychological Science, 28(5), 1259–1262. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1671-6981.2005.05.064.\nZhou, H., & Long, L. (2004). Statistical remedies for common method biases. Advances in Psychological Science, 12(6), 942–950. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1671-3710.2004.06.018.\nZhou, Y., Liu, Y., & Chen, J. (2015). Mediation role of self-control between mobile phone addiction and self-esteem. Chinese School Health, 36(7), 1032–1034 CNKI:SUN:XIWS.0.2015–07-025.",{"EN":89},"This study investigated the roles of implicit and explicit narcissism in the relationship between downward social comparison and mobile phone addiction. We randomly recruited 529 college students to complete the downward social comparison scale, mobile addiction tendency scale, and implicit and explicit narcissism questionnaires. Results showed that (1) downward social comparison positively related to implicit narcissism and mobile phone addiction but negatively related to explicit narcissism. Moreover, mobile phone addiction negatively related to explicit narcissism and positively related to implicit narcissism. (2) Downward social comparison positively predicted mobile phone addiction. (3) Implicit and explicit narcissism were parallel mediators in the relationship between downward social comparison and mobile phone addiction. Together, these results suggested that narcissism mediated the relationship of downward social comparison and mobile phone addiction of college students.",{"EN":91},"Does Downward Social Comparisons Affect Mobile Phone Addiction? 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M., Gray, K., & Martin-Sanchez, F. 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A. (1999). The self-regulation questionnaire. Retrieved from https:\u002F\u002Fcasaa.unm.edu\u002Finst\u002FSelfRegulation%20Questionnaire%20(SRQ).pdf. Accessed 06 Oct 2015.\nde Vries, H. J., Kooiman, T. J. M., van Ittersum, M. W., van Brussel, M., & de Groot, M. (2016). Do activity monitors increase physical activity in adults with overweight or obesity? A systematic review and meta-analysis. Obesity, 24(10), 2078–2091. https:\u002F\u002Fdoi.org\u002F10.1002\u002Foby.21619.\nGavora, P., Jakešová, J., & Kalenda, J. (2015). The Czech validation of the self-regulation questionnaire. Procedia-Social and Behavioral Sciences, 171, 222–230.\nHall, P. A., & Fong, G. T. (2007). Temporal self-regulation theory: A model for individual health behavior. Health Psychology Review, 1(1), 6–52. https:\u002F\u002Fdoi.org\u002F10.1080\u002F17437190701492437.\nHayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling [White paper]. Retrieved from http:\u002F\u002Fwww.afhayes.com\u002Fpublic\u002Fprocess2012.pdf. Accessed 11 Dec 2018.\nHermsen, S., Moons, J., Kerkhof, P., Wiekens, C., & Groot, M. D. (2017). Determinants for sustained use of an activity tracker: Observational study. JMIR mHealth and uHealth, 5(10), e164.\nJakesova, J., Gavora, P., & Kalenda, J. (2016). Self-regulation of behaviour: Students versus other adults. International Journal of Educational Psychology, 5(1), 56.\nKliemann, N., Vickerstaff, V., Croker, H., Johnson, F., Nazareth, I., & Beeken, R. J. (2017). The role of self-regulatory skills and automaticity on the effectiveness of a brief weight loss habit-based intervention: Secondary analysis of the 10 top tips randomised trial. International Journal of Behavioral Nutrition and Physical Activity, 14(1). https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs12966-017-0578-8.\nKluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284. https:\u002F\u002Fdoi.org\u002F10.1037\u002F0033-2909.119.2.254.\nKozak, A. T., Buscemi, J., Hawkins, M. A. W., Wang, M. L., Breland, J. Y., Ross, K. M., & Kommu, A. (2017). Technology-based interventions for weight management: Current randomized controlled trial evidence and future directions. Journal of Behavioral Medicine, 40(1), 99–111.\nKramer, J.-N., & Kowatsch, T. (2017). Using feedback to promote physical activity: The role of the feedback sign. Journal of Medical Internet Research, 19(6).\nLaRose, J. G., Lanoye, A., Tate, D. F., & Wing, R. R. (2016). Frequency of self-weighing and weight loss outcomes within a brief lifestyle intervention targeting emerging adults. Obesity Science & Practice, 2(1), 88–92.\nLee, I. M., Shiroma, E. J., Lobelo, F., Puska, P., Blair, S. N., Katzmarzyk, P. T., et al. (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. The Lancet, 380(9838), 219–229. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0140-6736(12)61031-9.\nLyons, E. J., Lewis, Z. H., Mayrsohn, B. G., & Rowland, J. L. (2014). Behavior change techniques implemented in electronic lifestyle activity monitors: A systematic content analysis. Journal of Medical Internet Research, 16(8), e192. https:\u002F\u002Fdoi.org\u002F10.2196\u002Fjmir.3469.\nMann, T., de Ridder, D., & Fujita, K. (2013). Self-regulation of health behavior: Social psychological approaches to goal setting and goal striving. Health Psychology, 32(5), 487–498. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fa0028533.\nMcKee, H., Ntoumanis, N., & Smith, B. (2013). Weight maintenance: Self-regulatory factors underpinning success and failure. Psychology and Health, 28(10), 1207–1223. https:\u002F\u002Fdoi.org\u002F10.1080\u002F08870446.2013.799162.\nMercer, K., Li, M., Giangregorio, L., Burns, C., & Grindrod, K. (2016). Behavior change techniques present in wearable activity trackers: A critical analysis. JMIR mHealth and uHealth, 4(2), e40. https:\u002F\u002Fdoi.org\u002F10.2196\u002Fmhealth.4461.\nMichie, S., Ashford, S., Sniehotta, F. F., Dombrowski, S. U., Bishop, A., & French, D. P. (2011). A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALO-RE taxonomy. Psychology & Health, 26(11), 1479–1498. https:\u002F\u002Fdoi.org\u002F10.1080\u002F08870446.2010.540664.\nMichie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46(1), 81–95.\nMichie, S., Atkins, L., & West, R. (2014). The behaviour change wheel: A guide to designing interventions. The Behavior Change Wheel: Book Launch Event.\nPacanowski, C. R., & Levitsky, D. A. (2015). Frequent self-weighing and visual feedback for weight loss in overweight adults. Journal of Obesity, 2015.\nQiu, S., Cai, X., Chen, X., Yang, B., & Sun, Z. (2014). Step counter use in type 2 diabetes: A meta-analysis of randomized controlled trials. BMC Medicine, 12(1), 36. https:\u002F\u002Fdoi.org\u002F10.1186\u002F1741-7015-12-36.\nRosenbaum, D. L., Espel, H. M., Butryn, M. L., Zhang, F., & Lowe, M. R. (2017). Daily self-weighing and weight gain prevention: A longitudinal study of college-aged women. Journal of Behavioral Medicine, 1–8.\nSamdal, G. B., Eide, G. E., Barth, T., Williams, G., & Meland, E. (2017). Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses. International Journal of Behavioral Nutrition and Physical Activity, 14(1), 42.\nSchembre, S. M., Liao, Y., Robertson, M. C., Dunton, G. F., Kerr, J., Haffey, M. E., Burnett, T., Basen-Engquist, K., & Hicklen, R. S. (2018). Just-in-time feedback in diet and physical activity interventions: Systematic review and practical design framework. Journal of Medical Internet Research, 20(3), e106.\nScholtens, S., Smidt, N., Swertz, M. A., Bakker, S. J. L., Dotinga, A., Vonk, J. M., et al. (2014). Cohort profile: LifeLines, a three-generation cohort study and biobank. International Journal of Epidemiology, 44(4), 1172–1180.\nSullivan, A. N., & Lachman, M. E. (2017). Behavior change with fitness technology in sedentary adults: A review of the evidence for increasing physical activity. Frontiers in Public Health, 4. https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffpubh.2016.00289.\nSuls, J., & Wallston, K. A. (2003). Social psychological foundations of health and illness. Blackwell series in health psychology and behavioral medicine. https:\u002F\u002Fdoi.org\u002F10.1002\u002F9780470753552.\nTeixeira, P. J., Carraa, E. V., Marques, M. M., Rutter, H., Oppert, J.-M., De Bourdeaudhuij, I., et al. (2015). Successful behavior change in obesity interventions in adults: A systematic review of self-regulation mediators. BMC Medicine, 13(1), 1.\nTully, M. A., Panter, J., & Ogilvie, D. (2014). Individual characteristics associated with mismatches between self-reported and accelerometer-measured physical activity. PLoS One, 9(6), e99636. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0099636.\nWhitehead, L., & Seaton, P. (2016). The effectiveness of self-management mobile phone and tablet apps in long-term condition management: A systematic review. Journal of Medical Internet Research, 18(5).\nZheng, Y., Klem, M. L., Sereika, S. M., Danford, C. A., Ewing, L. J., & Burke, L. E. (2015). Self-weighing in weight management: A systematic literature review. Obesity, 23(2), 256–265.\nZheng, Y., Sereika, S. M., Ewing, L. J., Danford, C. A., Terry, M. A., & Burke, L. E. (2016). Association between self-weighing and percent weight change: Mediation effects of adherence to energy intake and expenditure goals. Journal of the Academy of Nutrition and Dietetics, 116(4), 660–666.",{"EN":238},"Self-tracking of health may have positive effects on lifestyle behavior and weight loss; however, not much is known about the role of psychological processes in this effect. The purpose of this study was to assess to what extent a change in self-regulation capabilities can explain weight loss after 4 and 12 months of self-tracking physical activity and weight. An explorative cohort study was conducted with measurements at baseline (T0), 4 months (T1), and 12 months (T2). Healthy adult volunteers (N = 80) were included and provided with a digital weight scale and an activity tracker. Personal characteristics as well as the intention to change weight and physical activity were measured at T0. Self-regulation capabilities (goal orientation, self-direction, decision making, and impulse control) were measured with the Self-Regulation Questionnaire at T0, T1, and T2, together with body weight. At T0, all four dimensions of self-regulation were negatively related to BMI (p \u003C .01). At T1, weight significantly declined compared to T0 (− 2.0 kg\u002F− 0.64 kg\u002Fm2, p \u003C .001). At T2, this weight loss was maintained (− 1.8 kg\u002F− 0.57 kg\u002Fm2, p \u003C .01). At T1, intention to lose weight, self-weighing frequency, and an increase in goal orientation explained weight loss. At T2, an increase in decision making explained weight loss. Incremental self-regulation capabilities may explain weight loss after engaging in self-tracking of physical activity and weight. Future research should focus on exploring effective ways to further enhance self-regulation when using self-tracking technology and to assess the impact of different types of self-regulation stimuli on weight loss.",{"EN":240},"The Role of Self-Regulation in the Effect of Self-Tracking of Physical Activity and Weight on BMI",{"VOID":242},"10.1007\u002Fs41347-020-00127-w","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs41347-020-00127-w",[245,262,279,294,306,322],{"id":246,"sortIndex":50,"researcher":18,"roles":247,"affiliations":248,"properties":259},"91b8adef-c5cb-43e9-8a3c-748f01287d14",[102],[249],{"id":18,"sortIndex":19,"affiliation":250,"properties":18},{"id":251,"createTime":252,"updateTime":253,"relativeEntities":254,"slug":255,"properties":256,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"612783e2-0c40-4af2-8037-55259229fbf0","2023-12-07T06:51:51.798+00:00","2025-01-24T18:37:32.177+00:00",[],"Research-Group-Healthy-Ageing-Allied-Health-Care-and-Nursing-Hanze-University-of-Applied-Sciences-Groningen-The-Netherlands",{"title":257},{"VI":258},"Research Group Healthy Ageing, Allied Health Care and Nursing, Hanze University of Applied Sciences, Groningen, The Netherlands",{"title":260},{"VI":261},"Cees P. van der Schans",{"id":263,"sortIndex":53,"researcher":18,"roles":264,"affiliations":265,"properties":276},"56805438-230b-4956-9004-aaed5c61c007",[102],[266],{"id":18,"sortIndex":19,"affiliation":267,"properties":18},{"id":268,"createTime":269,"updateTime":270,"relativeEntities":271,"slug":272,"properties":273,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"fccdcb40-36e7-4486-a101-8cb62fa93d3c","2024-01-27T06:55:56.655+00:00","2024-09-19T23:07:32.549+00:00",[],"Department-of-Social-Psychology-University-of-Groningen-Groningen-The-Netherlands",{"title":274},{"VI":275},"Department of Social Psychology, University of Groningen, Groningen, The Netherlands",{"title":277},{"VI":278},"Arie Dijkstra",{"id":280,"sortIndex":43,"researcher":18,"roles":281,"affiliations":282,"properties":291},"d7ee3998-e96b-4f6f-bb22-73a5467dd36e",[102],[283],{"id":18,"sortIndex":19,"affiliation":284,"properties":18},{"id":285,"createTime":286,"updateTime":286,"relativeEntities":287,"slug":18,"properties":288,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"8f3e2aa9-a05e-474c-a2ba-2cd4002df0dd","2023-12-07T06:51:45.551+00:00",[],{"title":289},{"VI":290},"Department of Internal Medicine, Treant Care Group, Bethesda Diabetes Research Center & Bethesda General Hospital, Hoogeveen, The Netherlands",{"title":292},{"VI":293},"Adriaan Kooy",{"id":295,"sortIndex":19,"researcher":18,"roles":296,"affiliations":297,"properties":303},"14c2ebdc-9256-4e0f-b9ea-8c3b3597498d",[102],[298],{"id":18,"sortIndex":19,"affiliation":299,"properties":18},{"id":251,"createTime":252,"updateTime":253,"relativeEntities":300,"slug":255,"properties":301,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":302},{"VI":258},{"title":304},{"VI":305},"Thea J. 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H., & Craske, M. G. (2000). Mastery of your anxiety and panic (3rd ed.). San Antonio: Graywind Publications Inc\u002FThe Psychological Corporation.",{},{"id":18,"text":476,"url":18,"identifiers":477},"Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340.",{"doi":478},"10.2307\u002F249008",{"id":18,"text":480,"url":18,"identifiers":481},"Erbes, C. R., Stinson, R., Kuhn, E., Polusny, M., Urban, J., Hoffman, J., et al. (2014). Access, utilization, and interest in mHealth applications among veterans receiving outpatient care for PTSD. Military Medicine, 179(11), 1218–1222.",{"doi":482},"10.7205\u002FMILMED-D-14-00014",{"id":18,"text":484,"url":18,"identifiers":485},"Furukawa, T. A., Katherine Shear, M., Barlow, D. H., Gorman, J. M., Woods, S. W., Money, R., Etschel, E., Engel, R. R., & Leucht, S. (2009). Evidence-based guidelines for interpretation of the panic disorder severity scale. Depression and Anxiety, 26(10), 922–929.",{"doi":486},"10.1002\u002Fda.20532",{"id":18,"text":488,"url":18,"identifiers":489},"Heron, K. E., & Smyth, J. M. (2010). Ecological momentary interventions: incorporating mobile technology into psychosocial and health behaviour treatments. British Journal of Health Psychology, 15(1), 1–39.",{"doi":490},"10.1348\u002F135910709X466063",{"id":18,"text":492,"url":18,"identifiers":493},"Newman, M. G., Szkodny, L. E., Llera, S. J., & Przeworski, A. (2011). A review of technology-assisted self-help and minimal contact therapies for anxiety and depression: is human contact necessary for therapeutic efficacy? Clinical Psychology Review, 31(1), 89–103.",{"doi":494},"10.1016\u002Fj.cpr.2010.09.008",{"id":18,"text":496,"url":18,"identifiers":497},"Price, M., Yuen, E. K., Goetter, E. M., Herbert, J. D., Forman, E. M., Acierno, R., & Ruggiero, K. J. (2014). mHealth: a mechanism to deliver more accessible, more effective mental health care. Clinical Psychology and Psychotherapy, 21(5), 427–436.",{"doi":498},"10.1002\u002Fcpp.1855",{"id":18,"text":500,"url":18,"identifiers":501},"Riding-Malon, R., & Werth Jr., J. L. (2014). Psychological practice in rural settings: At the cutting edge. Professional Psychology: Research and Practice, 45(2), 85–91.",{"doi":502},"10.1037\u002Fa0036172",{"id":18,"text":504,"url":18,"identifiers":505},"Shear, M. K., Brown, T. A., Sholomskas, D. E., Barlow, D. H., Gorman, J. M., Woods, S. W., & Cloitre, M. (1992). Panic disorder severity scale (PDSS). Pittsburgh: Department of Psychiatry, University of Pittsburgh School of Medicine.",{},{"id":18,"text":507,"url":18,"identifiers":508},"Stecker, T., Fortney, J., Hamilton, F., Sherbourne, C. D., & Ajzen, I. (2010). Engagement in mental health treatment among veterans returning from Iraq. Patient preference and adherence, 4, 45–49.",{"doi":509},"10.2147\u002FPPA.S7368",{"id":18,"text":511,"url":18,"identifiers":512},"Teng, E. J., Barrera, T. 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The Journal of Alternative and Complementary Medicine, 21(2), 100–102.\nPlaza, I., Demarzo, M. M. P., Herrera-Mercadal, P., & García-Campayo, J. (2013). Mindfulness-based mobile applications: literature review and analysis of current features. JMIR MHealth and UHealth, 1(2), e24.\nRebedew, D. (2018). Five mobile apps for mindfulness. Family Practice Management, 25(3), 21–24.\nStatista. (2018). Most popular Apple App Store categories in May 2018, by share of available apps. Retrieved June 10, 2018 from https:\u002F\u002Fwww.statista.com\u002Fstatistics\u002F270291\u002Fpopular-categories-in-the-app-store\u002F.\nTan, C.-M. (2012). Search inside yourself: the unexpected path to achieving success, happiness (and world peace). New York: HarperOne.\nTang, Y. Y., Ma, Y., Wang, J., Fan, Y., Feng, S., Lu, Q., ..., Posner, M. I. (2007). Short-term mediation training improves attention and self-regulation. Proceedings of the National Academy of Sciences, 104(43), 17152-17156. doi:https:\u002F\u002Fdoi.org\u002F10.1073\u002Fpnas.0707678104\nWen, L., Sweeney, T., Welton, L., Trockel, M., & Katznelson, L. (2017). Encouraging mindfulness in medical house staff via smartphone app: a pilot study. Academic Psychiatry, 41(5), 646–650. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40596-017-0768-3.",{"EN":953},"",{"EN":955},"This yearlong study examined the impact of the 10% Happier phone app on levels of mindfulness and perceived stress among academic advisors. In addition, the study explored whether attending a one-time training session would influence app usage. To date, there is limited research regarding the effectiveness of mindfulness apps on the levels of mindfulness and perceived stress and the impact an in-person mindfulness training has on app usage. In this study, participants were given the choice to attend a one-time training session that included gaining access to the app or receive access to the app without attending training. A quantitative design was used to sample academic advisors (n = 33) at a large, state university in the Midwest. The results showed that in-person training appeared to increase app usage, and paired sample t-tests indicated increased levels of mindfulness on the Mindfulness Attention and Awareness Scale (MAAS) and decreased levels of perceived stress on the Perceived Stress Scale (PSS) among app users. There was no significant difference in changes in levels of mindfulness and perceived stress among those who did not use the app. A final result indicated 85% of participants agreed that practicing mindfulness was beneficial to their self-care and well-being.",{"EN":957},"Evaluating the Effectiveness of a Mindfulness App Among Academic 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Telemedicine and geriatric psychiatry: directions for future research and policy. Journal of Geriatric Psychiatry and Neurology, 14, 59–62.\nLoh, P. K., Ramesh, P., Maher, S., et al. (2004). Can patients with dementia be assessed at a distance? The use of telehealth and standardized assessments. Internal Medicine Journal, 34, 239e242.\nConn, D. K., Madan, R., Lam, J., et al. (2013). Program evaluation of a telepsychiatry service for older adults connecting a university-affiliated geriatric center to a rural psychogeriatric outreach service in Northwest Ontario, Canada. International Psychogeriatrics, 25, 1795–1800.\nTsuji, M., Miyahara, S., Taoka, F., et al. (2001). An estimation of economic effects of tele-home care: hospital cost-savings of the elderly. Medinfo, 10(pt 1), 858–862.\nRabinowitz, T., Murphy, K. M., Amour, J. L., et al. (2010). Benefits of telepsychiatry consultation service for rural nursing home residents. Telemed J E Health, 16, 34–40.\nJohnston, D., & Jones III, B. N. (2001). Telepsychiatry consultations to a rural nursing facility: a 2-year experience. Journal of Geriatric Psychiatry and Neurology, 14, 72–75.\nInstitute of Medicine. (2000). Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academies Press.\nAnsak, M., & Zawadski, R. (1983). On Lok CCODA: a consolidated model. Home Health Care Services Quarterly, 4, 147–170.\nBodenheimer, T. (1999). Long-term care for frail elderly people—the on Lok model. The New England Journal of Medicine, 341, 1324–1328.\nEng, C., Pedulla, J., Eleazer, G. P., et al. (1997). Program of All-inclusive Care for the Elderly (PACE): an innovative model of integrated geriatric care and financing. Journal of the American Geriatrics Society, 45, 223–232.\nDoste, T. (1987). On Lok: replicating a capitated LTC program. Hospitals, 5, 112.\nTrice, L. (2006). PACE: a model for providing comprehensive healthcare for frail elders. Generations, 30, 90–92.\nNational PACE Association: PACE Providers. Available at: www.npaonline.org. Accessed July 26, 2016\nRovner, B. W., Kafonek, S., Filipp, L., et al. (1986). Prevalence of mental illness in a community nursing home. The American Journal of Psychiatry, 143(11), 1446–1449.\nFullerton, C. A., McGuire, T. G., Feng, Z., et al. (2009). Trends in mental health admissions to nursing homes: 1999–2005. Psychiatric Services, 60(7), 865–971.\nEden, J., Le, M., Maslow, K., et al. (2012). The mental health and substance use workforce for older adults: in whose hands? Washington, DC: National Academies Press.\nParmelee, P. A., Katz, I. R., & Lawton, M. P. (1989). Depression among institutionalized aged: assessment and prevalence estimation. Journal of Gerontology, 44(1), M22–M29.\nGinsburg, I. F., & Eng, C. (2009). On-site mental health services for PACE (Program of All-inclusive Care for the Elderly) centers. Journal of the American Medical Directors Association, 10, 277–280. doi:10.1016\u002Fj.jamda.2009.02.013.\nWieland, D., Lamb, V., Wang, H., et al. (2000). Participants in the Program of All-Inclusive Care for the Elderly (PACE) demonstration developing disease–impairment–disability profiles. The Gerontologist, 40(2), 218–227.\nCacchione, P. Z., Eible, L., & Huege, S. F. (2016). Person-centered care for older adults with serious mental illness and substance misuse within a Program of All-Inclusive Care for the Elderly. Journal of Gerontological Nursing, 42(5), 11–17.\nU.S. Census Bureau Census Quickfacts. Available at http:\u002F\u002Fquickfacts.census.gov\u002Fqfd\u002Fstates\u002F45\u002F45075.html. Accessed July 26, 2016",{"EN":1267},"The older adult population is growing. Limited numbers and access to trained geriatric psychiatrists hinder access to timely and appropriate geriatric mental health care, particularly in rural areas. Programs for All-Inclusive Care of the Elderly (PACE) provide person-centered care to nursing home-eligible community-dwelling elderly, in whom mental health conditions including dementia and depression are highly prevalent. However, access to mental health care across PACE programs remains an under-resourced need. Telepsychiatry, the exchange of health care-related information and delivery of psychiatric services using videoconferencing technology (VCT) from a distance is one vehicle to reduce this barrier. The Institute of Medicine has identified the importance of telehealth technologies to enhance access to and quality care for older adults, particularly those in rural areas of the USA. This report describes the development and implementation of a geriatric telepsychiatry consultation service between an academic medical center and a rural PACE program.",{"EN":1269},"Bridging the Gap: Geriatric Telepsychiatry Consultations to a Rural PACE Program",{"VOID":1271},"10.1007\u002Fs41347-017-0013-7","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs41347-017-0013-7",[1274],{"id":1275,"sortIndex":19,"researcher":18,"roles":1276,"affiliations":1277,"properties":1286},"146e76e2-4e4e-4f0c-9524-edd61e93f49b",[102],[1278],{"id":18,"sortIndex":19,"affiliation":1279,"properties":18},{"id":1280,"createTime":1281,"updateTime":1281,"relativeEntities":1282,"slug":18,"properties":1283,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"896492ca-54df-4388-aafa-940490a6b719","2024-01-05T22:53:15.324+00:00",[],{"title":1284},{"VI":1285},"Department of Neuropsychiatry and Behavioral Sciences, Palmetto Health- USC Medical Group, University of South Carolina School of Medicine, Columbia, USA",{"title":1287},{"VI":1288},"Shilpa Srinivasan",{"url":1272,"publisher":1290,"properties":1309},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1291,"slug":10,"properties":1292,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1295,"manageAffiliations":1296,"indexDatabases":1297,"url":40,"thumbnailPath":18,"statistic":1304,"gsStatistic":18,"type":74,"analyzePriority":18},[],{"issn":1293,"title":1294},{"VOID":13},{"EN":15},[],[],[1298],{"id":24,"indexDatabase":1299,"url":37,"indexYears":38,"academicFieldIds":18,"indexDatabaseRanking":39},{"id":26,"createTime":27,"updateTime":28,"relativeEntities":1300,"label":1301,"description":1302,"key":34,"publicationTags":1303,"standard":18},[],{"EN":31,"VI":31},{"EN":31,"VI":33},[36],{"impactFactor":19,"impactFactorByYear":1305,"i10Index":49,"i10IndexLast5Year":50,"totalPublication":51,"totalPublicationByYear":1306,"totalCitation":61,"totalCitationByYear":1307,"totalCitationPerPublication":66,"totalCitationPerPublicationByYear":1308,"hindexLast5Year":73,"hindex":73},{"2017":43,"2018":44,"2019":45,"2020":46,"2021":47,"2022":48,"2023":47},{"2016":53,"2017":54,"2018":54,"2019":55,"2020":56,"2021":57,"2022":58,"2023":59,"2024":60},{"2016":63,"2017":56,"2018":56,"2019":64,"2020":65,"2021":60,"2022":63},{"2016":63,"2017":68,"2018":68,"2019":69,"2020":70,"2021":71,"2022":72},{"volume":1310,"pages":1312},{"VOID":1311},"2",{"VOID":1313},"77-83","2017-02-03",2017,{"id":1317,"createTime":1318,"updateTime":1318,"relativeEntities":1319,"slug":18,"properties":1320,"entityType":94,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1327,"fullTextUrl":18,"authors":1328,"publicationType":199,"publisherRelationship":1417,"citationCount":18,"citationInfo":18,"publishDate":1442,"publishYear":1443,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":18,"openAccess":18,"references":18,"isForceReanalyzing":227},"6b28d0da-33ae-4845-bf6e-67e901efa986","2024-02-12T22:46:40.740+00:00",[],{"references":1321,"title":1323,"doi":1325},{"VOID":1322},"Armstrong, C. M. (2019). Mobile health provider training: Results and lessons learned from year four of training on core competencies for mobile health in clinical care. Journal of Technology and Behavioral Science, 4, 86–92. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs41347-019-00089-8\nArmstrong, C. M., McGee-Vincent, P., Juhasz, K., Owen, J., Avery, T., Jaworski, B., & Hilty, D. M. (2021). VA Mobile Health Practice Guide (1st ed.). U.S. Department of Veterans Affairs.\nChen, K., & Chan, A. H. S. (2014). Gerontechnology acceptance by elderly Hong Kong Chinese: A senior technology acceptance model (STAM). Ergonomics, 57, 635–652. https:\u002F\u002Fdoi.org\u002F10.1080\u002F00140139.2014.895855\nConnolly, S. L., Hogan, T. P., Shimada, S. L., & Miller, C. J. (2021). Leveraging implementation science to understand factors influencing sustained use of mental health apps: A narrative review. Journal of Technology and Behavioral Science, 6, 184–196. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs41347-020-00165-4\nDavis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003. https:\u002F\u002Fdoi.org\u002F10.1287\u002Fmnsc.35.8.982\nFortuna, K. L., Brooks, J. M., Umucu, E., Walker, R., & Chow, P. I. (2019). Peer support: A human factor to enhance engagement in digital health behavior change interventions. Journal of Technology and Behavioral Science, 4, 152–161. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs41347-019-00105-x\nGould, C. E., & Hantke, N. C. (2020). Promoting technology and virtual visits to improve older adult mental health in the face of COVID-19. American Journal of Geriatric Psychiatry, 28, 889–890. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jagp.2020.05.011\nGould, C. E., Kok, B. C., Ma, V. K., Zapata, A. M. L., Owen, J. E., & Kuhn, E. (2019). Veterans Affairs and the Department of Defense mental health apps: A systematic literature review. Psychological Services, 16, 196–207. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fser0000289\nGould, C. E., Loup, J., Kuhn, E., Beaudreau, S. A., Ma, F., Goldstein, M. K., Wetherell, J. L., Zapata, A. M. L., Choe, P., & O’Hara, R. (2020a). Technology use and preferences for mental health self-management interventions among older veterans. International Journal of Geriatric Psychiatry, 35, 321–330. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fgps.5252\nGould, C. E., Loup, J. R., Scales, A. N., Juang, C., Carlson, C., Ma, F., & Sakai, E. Y. (2020b). Development and refinement of educational materials to help older veterans use VA mental health mobile apps. Professional Psychology: Research and Practice, 51, 414–423. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fpro0000354\nGuest, G., MacQueen, K. M., & Namey, E. E. (2012). Applied thematic analysis. Los Angeles, CA: SAGE.\nKarel, M. J., Wray, L. O., Adler, G., Hannum, A. O., Luci, K., Brady, L. A., & McGuire, M. H. (2020). Mental health needs of aging veterans: Recent evidence and clinical recommendations. Clinical Gerontologist. https:\u002F\u002Fdoi.org\u002F10.1080\u002F07317115.2020.1716910\nLipschitz, J., Miller, C. J., Hogan, T. P., Burdick, K. E., Lippin-Foster, R., Simon, S. R., & Burgess, J. (2019). Adoption of mobile apps for depression and anxiety: Cross-sectional survey study on patient interest and barriers to engagement. JMIR Mental Health, 6(1), e11334. https:\u002F\u002Fdoi.org\u002F10.2196\u002F11334\nMiller, K. E., Kuhn, E., Yu, J., Owen, J. E., Jaworski, B. K., Taylor, K., Blonigen, D. M., & Possemato, K. (2019). Use and perceptions of mobile apps for patients among VA primary care mental and behavioral health providers. Professional Psychology: Research and Practice, 50, 204. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fpro0000229\nMontena, A. L., Possemato, K., Kuhn, E., Carlson, E. B., McGovern, M., Smith, J., & Blonigen, D. (2021). Barriers and facilitators to peer-supported implementation of mental health mobile applications with veterans in primary care. Journal of Technology in Behavioral Science. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs41347-021-00198-3\nNational Center for Veterans Analysis and Statistics, Veteran Population. (2020). https:\u002F\u002Fwww.va.gov\u002Fvetdata\u002Fveteran_population.asp. Accessed 5 Feb 2021.\nOwen, J. E., Kuhn, E., Jaworski, B. K., McGee-Vincent, P., Juhasz, K., Hoffman, J. E., & Rosen, C. (2018). VA mobile apps for PTSD and related problems: Public health resources for veterans and those who care for them. The Journal of mHealth. https:\u002F\u002Fdoi.org\u002F10.21037\u002Fmhealth.2018.05.07\nReger, G. M., Browne, K. C., Campellone, T. R., Simons, C., Kuhn, E., Fortney, J. C., Sayre, G. G., & Reisinger, H. S. (2017). Barriers and facilitators to mobile application use during PTSD treatment: Clinician adoption of PE coach. Professional Psychology: Research and Practice, 48(6), 510–517. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fpro0000153\nReger, G. M., Harned, M., Stevens, E. S., Porter, S., Nguyen, J., & Norr, A. M. (2021). Mobile applications may be the future of veteran mental health support but do veterans know yet? A survey of app knowledge and use. Psychological Services. https:\u002F\u002Fdoi.org\u002F10.1037\u002Fser0000562\nSlightam, C., Gregory, A. J., Hu, J., Jacobs, J., Gurmessa, T., Kimerling, R., Blonigen, D., & Zulman, D. M. (2020). Patient perceptions of video visits using Veterans Affairs telehealth tablets: Survey study. Journal of Medical Internet Research, 22, e15682. https:\u002F\u002Fdoi.org\u002F10.2196\u002F15682\nUnutzer, J., Katon, W., Callahan, C. M., Williams, J. W. J., Hunkeler, E., Harpole, L., Hoffing, M., Della Penna, R. D., Noel, P. H., Lin, E. H. B., Arean, P. A., Hegel, M. T., Tang, L., Belin, T. R., Oishi, S., & Langston, C. (2002). Collaborative care management of late-life depression in the primary care setting: A randomized controlled trial. JAMA, 288, 2836–2845. https:\u002F\u002Fdoi.org\u002F10.1001\u002Fjama.288.22.2836\nWang, K., Varma, D. S., & Prosperi, M. (2018). A systematic review of the effectiveness of mobile apps for monitoring and management of mental health symptoms or disorders. Journal of Psychiatry Research, 107, 73–78. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jpsychires.2018.10.006\nWisniewski, H., & Torous, J. (2020). Digital navigators to implement smartphone and digital tools in care. Acta Psychiatrica Scandinavica, 141, 350–355. https:\u002F\u002Fdoi.org\u002F10.1111\u002Facps.13149",{"EN":1324},"Connecting Older Veterans with Mental Health Mobile Apps: a Survey of Provider and Staff Use of Apps and Patient Education Materials",{"VOID":1326},"10.1007\u002Fs41347-021-00236-0","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs41347-021-00236-0",[1329,1344,1359,1381,1393,1405],{"id":1330,"sortIndex":50,"researcher":18,"roles":1331,"affiliations":1332,"properties":1341},"8d053469-f40e-4052-847c-4aac6b71dc46",[102],[1333],{"id":18,"sortIndex":19,"affiliation":1334,"properties":18},{"id":1335,"createTime":1336,"updateTime":1336,"relativeEntities":1337,"slug":18,"properties":1338,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"97c22639-79fa-4fc1-894a-80e2ce44a868","2024-02-12T22:46:40.883+00:00",[],{"title":1339},{"VI":1340},"Geriatric Research Education and Clinical Center, GRECC (182B), VA Palo Alto Health Care System, Palo Alto, USA",{"title":1342},{"VI":1343},"Ana Jessica Alfaro",{"id":1345,"sortIndex":308,"researcher":18,"roles":1346,"affiliations":1347,"properties":1356},"96951ba1-1df7-4f07-9ab0-ae268c99cfe9",[102],[1348],{"id":18,"sortIndex":19,"affiliation":1349,"properties":18},{"id":1350,"createTime":1351,"updateTime":1351,"relativeEntities":1352,"slug":18,"properties":1353,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"465cc989-9d93-45cf-9c58-291097d6a2d0","2024-02-12T22:46:41.071+00:00",[],{"title":1354},{"VI":1355},"Psychology Service, VA Palo Alto Health Care System, Palo Alto, USA",{"title":1357},{"VI":1358},"Erin Y. Sakai",{"id":1360,"sortIndex":19,"researcher":18,"roles":1361,"affiliations":1362,"properties":1378},"bc01e7aa-1ba0-4ebb-8aef-67f7d8ea3b79",[102],[1363,1368],{"id":18,"sortIndex":19,"affiliation":1364,"properties":18},{"id":1335,"createTime":1336,"updateTime":1336,"relativeEntities":1365,"slug":18,"properties":1366,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":1367},{"VI":1340},{"id":1369,"sortIndex":53,"affiliation":1370,"properties":1377},"f68bde95-4b3f-408d-8643-04eaeb219bea",{"id":1371,"createTime":1372,"updateTime":1372,"relativeEntities":1373,"slug":18,"properties":1374,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"5107efec-0a46-4840-82cd-2aa0114c87bb","2024-02-05T16:12:15.508+00:00",[],{"title":1375},{"VI":1376},"Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Palo Alto, USA",{},{"title":1379},{"VI":1380},"Christine E. Gould",{"id":1382,"sortIndex":181,"researcher":18,"roles":1383,"affiliations":1384,"properties":1390},"af4c2b20-38cd-4d5d-a107-b3c39e345ee9",[102],[1385],{"id":18,"sortIndex":19,"affiliation":1386,"properties":18},{"id":1350,"createTime":1351,"updateTime":1351,"relativeEntities":1387,"slug":18,"properties":1388,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":1389},{"VI":1355},{"title":1391},{"VI":1392},"Jason R. Anderson",{"id":1394,"sortIndex":53,"researcher":18,"roles":1395,"affiliations":1396,"properties":1402},"205963d1-79e5-47ab-9c1b-5529c8885f10",[102],[1397],{"id":18,"sortIndex":19,"affiliation":1398,"properties":18},{"id":1335,"createTime":1336,"updateTime":1336,"relativeEntities":1399,"slug":18,"properties":1400,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":1401},{"VI":1340},{"title":1403},{"VI":1404},"Priyanka S. Mehta",{"id":1406,"sortIndex":43,"researcher":18,"roles":1407,"affiliations":1408,"properties":1414},"92046a25-5842-4f04-bcdc-7839e22be8fb",[102],[1409],{"id":18,"sortIndex":19,"affiliation":1410,"properties":18},{"id":1335,"createTime":1336,"updateTime":1336,"relativeEntities":1411,"slug":18,"properties":1412,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},[],{"title":1413},{"VI":1340},{"title":1415},{"VI":1416},"Chalise Carlson",{"url":1327,"publisher":1418,"properties":1437},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1419,"slug":10,"properties":1420,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1423,"manageAffiliations":1424,"indexDatabases":1425,"url":40,"thumbnailPath":18,"statistic":1432,"gsStatistic":18,"type":74,"analyzePriority":18},[],{"issn":1421,"title":1422},{"VOID":13},{"EN":15},[],[],[1426],{"id":24,"indexDatabase":1427,"url":37,"indexYears":38,"academicFieldIds":18,"indexDatabaseRanking":39},{"id":26,"createTime":27,"updateTime":28,"relativeEntities":1428,"label":1429,"description":1430,"key":34,"publicationTags":1431,"standard":18},[],{"EN":31,"VI":31},{"EN":31,"VI":33},[36],{"impactFactor":19,"impactFactorByYear":1433,"i10Index":49,"i10IndexLast5Year":50,"totalPublication":51,"totalPublicationByYear":1434,"totalCitation":61,"totalCitationByYear":1435,"totalCitationPerPublication":66,"totalCitationPerPublicationByYear":1436,"hindexLast5Year":73,"hindex":73},{"2017":43,"2018":44,"2019":45,"2020":46,"2021":47,"2022":48,"2023":47},{"2016":53,"2017":54,"2018":54,"2019":55,"2020":56,"2021":57,"2022":58,"2023":59,"2024":60},{"2016":63,"2017":56,"2018":56,"2019":64,"2020":65,"2021":60,"2022":63},{"2016":63,"2017":68,"2018":68,"2019":69,"2020":70,"2021":71,"2022":72},{"volume":1438,"pages":1440},{"VOID":1439},"7",{"VOID":1441},"192-197","2021-11-23",2021,{"id":1445,"createTime":1446,"updateTime":1447,"relativeEntities":1448,"slug":1449,"properties":1450,"entityType":94,"verifyStatus":95,"verifyTime":1447,"verifyNote":96,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1459,"fullTextUrl":18,"authors":1460,"publicationType":199,"publisherRelationship":1577,"citationCount":18,"citationInfo":18,"publishDate":1601,"publishYear":1315,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":18,"openAccess":18,"references":18,"isForceReanalyzing":227},"6f353fe8-dc4b-42be-9ca9-0ce846c325a1","2024-01-01T15:28:50.923+00:00","2025-01-16T22:32:48.839+00:00",[],"Machine-Learning-for-Identifying-Emotional-Expression-in-Text-Improving-the-Accuracy-of-Established-Methods",{"references":1451,"abstract":1453,"title":1455,"doi":1457},{"VOID":1452},"Alm CO, Roth D, Sproat R. 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Detecting emotional contagion in massive social networks. PloS One, 9(3), e90315.\nEkman, P. (1999). Basic emotions. In T. Dalgleish & T. Power (Eds.), The handbook of cognition and emotion (pp. 45–60). Cichester: John Wiley.\nElhadad N., Zhang S., Driscoll P., & Brody S. (2014). Characterizing the sublanguage of online breast cancer forums medication, symptoms, and emoticons. AMIA Fall Symposium, pp 516–525.\nEpley, N., & Kruger, J. (2005). When what you type isn’t what they read: the perseverance of stereotypes and expectancies over email. Journal of Experimental Social Psychology, 41, 414–422.\nGiese-Davis, J., Piemme, K. A., Dillon, C., & Twirbutt, S. (2005). Macro-variables in affective expression in women with breast cancer participating in support groups. In J. A. Harrigan, R. Rosenthal, & K. R. Schere (Eds.), Nonverbal behavior in the affective sciences: a handbook of research methods (pp. 399–445). Oxford: Oxford University Press.\nGottman, J. M. (1994). What predicts divorce? The relationship between marital processes and marital outcomes. Hillsdale, NJ: Lawrence Erlbaum Associates.\nHonkalampi, K., Hintikka, J., Tanskanen, A., Lehtonen, J., & Viinamaki, H. (2000). Depression is strongly associated with alexithymia in the general population. Journal of Psychosomatic Research, 48, 99–104.\nJha, Mukund, and Noémie Elhadad. Cancer stage prediction based on patient online discourse. In Proceedings of the 2010 Workshop on Biomedical Natural Language Processing, pp. 64–71. Association for Computational Linguistics, 2010.\nKemeny, M. E., Foltz, C., Cavanagh, J. F., Cullen, M., Giese-Davis, J., Jennings, P., Rosenberg, E. L., Gillath, O., Shaver, P. R., Wallace, B. A., & Ekman, P. (2012). Comtemplative\u002Femotion training reduces negative emotional behavior and promotes prosocial responses. Emotion, 12(2), 338–350.\nKramer, A. D., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences, 111, 8788–8790.\nLewallen, A. C., Owen, J. E., Bantum, E. O., & Stanton, A. L. (2014). How language affects peer responsiveness in an online cancer support group: implications for treatment design and facilitation. Psycho-Oncology, 23, 766–772.\nLiess, A., Simon, W., Yutsis, M., Owen, J. E., Piemme, K. A., Golant, M., & Giese-Davis, J. (2008). Detecting emotional expression in face-to-face and online breast cancer support groups. Journal of Consulting and Clinical Psychology, 76, 517–523.\nLumley, M. A., Ovies, T., Stettner, L., Wehmer, F., & Lakey, B. (1996). Alexithymia, social support, and health problems. Journal of Psychosomatic Research, 41, 519–530.\nMadhyastha, T. M., Hamaker, E. L., & Gottman, J. M. (2011). Investigating spousal influence using moment-to-moment affect data from marital conflict. Journal of Family Psychology, 22(2), 292–300.\nMattila, A. K., Saarni, S. I., Salminen, J. K., Huhtala, H., Sintonen, H., & Joukamaa, M. (2009). Alexithymia and health-related quality of life in the general population. Psychosomatics, 50, 59–68.\nNeviarouskaya, A., Prendinger, H., & Ishizuka, M. (2010). Recognition of fine-grained emotions from text: an approach based on the compositionality principle. In T. Nishida et al. (Eds.), Modeling machine emotions for realizing intelligence (pp. 179–207). Berlin: Springer.\nNygaard, L. C., & Lunders, E. R. (2002). Resolution of lexical ambiguity by emotional tone of voice. Memory & Cognition, 30, 583–593.\nOwen, J. E., Hanson, E., Preddy, D. A., & Bantum, E. O. (2011). Linguistically-tailored video feedback increases total and positive emotional expression in a structured writing task. Computers in Human Behavior, 27(2), 874–882.\nOwen J.E., Bantum E.O., Criswell K., Bazzo J., Gorlick A., & Stanton A. (2013). Representativeness of two sampling procedures for an internet intervention targeting cancer related distress: a comparison of convenience and registry samples. Journal of Behavioral Medicine, [Epub ahead of print]\nOwen, J. E., Bantum, E. O., Gorlick, A., & Stanton, A. L. (2014). Engagement with a social-networking intervention for cancer-related distress. Annals of Behavioral Medicine, September, 11, 1–11.\nPang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135.\nPennebaker, J. W. (1997). Writing about emotional experiences as a therapeutic process. Psychological Science, 8, 162–166.\nStanton, A. L., Danoff-Burg, S., Cameron, C. L., Bishop, M., Collins, C. A., Kirk, S. B., Sworowski, L. A., & Twillman, R. (2000). Emotionally expressive coping predicts psychological and physical adjustment to breast cancer. Journal of Consulting and Clinical Psychology, 68, 875–882.\nTamagawa, R., Li, Y., Gravity, T., Piemme, K., DiMiceli, S., Collie, K., & Giese Davis, J. (2015). Deconstructing therapeutic mechanisms in cancer support groups: do we express more emotion when we tell stories or talk directly to each other? Journal of Behavioral Medicine, 38(1), 171–182.\nTausczik, Y., Faasse, K., Pennebaker, J. W., & Petrie, K. J. (2012). Public anxiety and information-seeking following the H1N1 outbreak: Blogs, newspaper articles, and Wikipedia visits. Health Communication, 27, 179–185.\nVan Kleef, G. A., van den Berg, H., & Heerdink, M. W. (2015). The persuasive power of emotions: effects of emotional expressions on attitude formation and change. Journal of Applied Psychology, 100, 1124–1142.\nThe Stanford Natural Language Processing Group. (2006). Stanford Named Entity Recognizer (NER). Retrieved from: http:\u002F\u002Fnlp.stanford.edu\u002Fsoftware\u002FCRF-NER.shtml",{"EN":1454},"Expression of emotion has been linked to numerous critical and beneficial aspects of human functioning. Accurately capturing emotional expression in text grows in relevance as people continue to spend more time in an online environment. The Linguistic Inquiry and Word Count (LIWC) is a commonly used program for the identification of many constructs, including emotional expression. In an earlier study by Bantum and Owen (Psychol. Assess. 21:79–88, 2009), LIWC was demonstrated to have good sensitivity yet poor positive predictive value. The goal of the current study was to create an automated machine learning technique to mimic manual coding. The sample included online support groups, cancer discussion boards, and transcripts from an expressive writing study, which resulted in 39,367 sentence-level coding decisions. In examining the entire sample, the machine learning approach outperformed LIWC, in all categories outside of sensitivity for negative emotion (LIWC sensitivity = 0.85; machine learning sensitivity = 0.41), although LIWC does not take into consideration prosocial emotion, such as affection, interest, and validation. LIWC performed significantly better than the machine learning approach when removing the prosocial emotions (p = \u003C.0001). The sample overrepresented examples of emotion that fit into the overarching category of positive emotion. Remaining work is needed to create more effective machine learning features for codes that are thought to be important emotionally but were not well represented in the sample (e.g., frustration, contempt, and belligerence), and machine learning could be a fruitful method for continued exploration.",{"EN":1456},"Machine Learning for Identifying Emotional Expression in Text: Improving the Accuracy of Established Methods",{"VOID":1458},"10.1007\u002Fs41347-017-0015-5","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs41347-017-0015-5",[1461,1476,1491,1506,1521,1536,1553,1565],{"id":1462,"sortIndex":43,"researcher":18,"roles":1463,"affiliations":1464,"properties":1473},"6e3d10a8-afbb-45b4-be5b-74098b06c106",[102],[1465],{"id":18,"sortIndex":19,"affiliation":1466,"properties":18},{"id":1467,"createTime":1468,"updateTime":1468,"relativeEntities":1469,"slug":18,"properties":1470,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"2c88e137-7574-41c5-902c-22bba191765f","2024-01-01T15:28:51.022+00:00",[],{"title":1471},{"VI":1472},"Dissemination & Training Division, VA Palo Alto Health Care System, Livermore, USA",{"title":1474},{"VI":1475},"Jason E. Owen",{"id":1477,"sortIndex":19,"researcher":18,"roles":1478,"affiliations":1479,"properties":1488},"085bdf27-abb0-4950-9cf0-e277a73a2bb2",[102],[1480],{"id":18,"sortIndex":19,"affiliation":1481,"properties":18},{"id":1482,"createTime":1483,"updateTime":1483,"relativeEntities":1484,"slug":18,"properties":1485,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"f4639122-5f51-4cb6-bab6-0299c39a9455","2024-01-01T15:28:50.951+00:00",[],{"title":1486},{"VI":1487},"Cancer Prevention & Control Program, University of Hawaii Cancer Center, Honolulu, USA",{"title":1489},{"VI":1490},"Erin O’Carroll Bantum",{"id":1492,"sortIndex":181,"researcher":18,"roles":1493,"affiliations":1494,"properties":1503},"d6108ba6-4131-4c92-b890-cd7926f9230e",[102],[1495],{"id":18,"sortIndex":19,"affiliation":1496,"properties":18},{"id":1497,"createTime":1498,"updateTime":1498,"relativeEntities":1499,"slug":18,"properties":1500,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"e45a102f-6e1e-4fd4-91c1-73d4d6c64f77","2024-01-01T15:28:50.999+00:00",[],{"title":1501},{"VI":1502},"Biomedical Informatics, Columbia University, New York, USA",{"title":1504},{"VI":1505},"Shaodian Zhang",{"id":1507,"sortIndex":308,"researcher":18,"roles":1508,"affiliations":1509,"properties":1518},"4001d37c-da55-437c-8e71-1fc168997e46",[102],[1510],{"id":18,"sortIndex":19,"affiliation":1511,"properties":18},{"id":1512,"createTime":1513,"updateTime":1513,"relativeEntities":1514,"slug":18,"properties":1515,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"5b15a121-e2d1-4cd2-bc62-648391d0ab27","2024-01-01T15:28:51.137+00:00",[],{"title":1516},{"VI":1517},"Cancer Support Community, Washington, USA",{"title":1519},{"VI":1520},"Joanne Buzaglo",{"id":1522,"sortIndex":49,"researcher":18,"roles":1523,"affiliations":1524,"properties":1533},"8d82aae6-3d33-4338-9adb-4cb11a4e2a56",[102],[1525],{"id":18,"sortIndex":19,"affiliation":1526,"properties":18},{"id":1527,"createTime":1528,"updateTime":1528,"relativeEntities":1529,"slug":18,"properties":1530,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"12caf4cb-798f-4110-97b1-199c420189d8","2024-01-14T05:16:59.099+00:00",[],{"title":1531},{"VI":1532},"Cumming School of Medicine, Department of Oncology, University of Calgary, Calgary, Canada",{"title":1534},{"VI":1535},"Janine Giese-Davis",{"id":1537,"sortIndex":1538,"researcher":18,"roles":1539,"affiliations":1540,"properties":1550},"10b68be3-066d-4d13-8e97-5394eaf76e95",6,[102],[1541],{"id":18,"sortIndex":19,"affiliation":1542,"properties":18},{"id":1543,"createTime":1544,"updateTime":1544,"relativeEntities":1545,"slug":1546,"properties":1547,"entityType":113,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"syncStatus":17,"languages":18,"translateLanguages":18,"viewCount":19},"b33dd48a-3d19-4d58-9ea1-6447d72a409a","2024-04-18T02:01:02.699+00:00",[],"Alberta-Health-Services-Calgary-Canada",{"title":1548},{"EN":1549},"Alberta Health Services, Calgary, Canada",{"title":1551},{"VI":1552},"Joanne 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A., Cavaliere, A., Carraresi, L., & Stranieri, S. (2014). Food SMEs face increasing competition in the EU market: marketing management capability is a tool for becoming a price maker. Agribusiness, 30(2), 113–131.\nBlock, J., Sandner, P., & Spiegel, F. (2015). How do risk attitudes differ within the group of entrepreneurs? The role of motivation and procedural utility. Journal of Small Business Management, 53(1), 183–206.\nBower, J. L., & Christensen, C. M. (1995). Disruptive technologies: catching the wave. Harvard Business Review, 73(1), 43–53.\nCavanagh, A., Freeman, S., Kalfadellis, P., & Herbert, K. (2017). Assigned versus assumed: towards a contemporary, detailed understanding of subsidiary autonomy. International Business Review, 26, 1168–1183.\nChallagalla, G., Murtha, B., & Jaworski, B. (2014). Marketing doctrine: a principle-based approach to guiding marketing decision making in firms. Journal of Marketing, 78, 4–20.\nChen, J., Neubaum, D. O., Reilly, R. R., & Lynn, G. S. (2015). The relationship between team autonomy and new product development performance under different levels of technological turbulence. Journal of Operations Management, 33-34, 83–96.\nDedrick, J., Gurbaxani, V., & Kraemer, K. (2003). Information technology and economic performance: a critical review of the empirical evidence. ACM Computing Survey, 35(1), 1–28.\nDemir, M., McNeese, J., & Cooke, N. J. (2017). Team situation awareness within the context of human-autonomy teaming. Cognitive System Research, 46, 3–12.\nDidonet, S., Simmons, G., Díaz-Villavicencio, G., & Palmer, M. (2012). Firms with capability to leverage substantial technological resources to come up innovation. Marketing Intelligence & Planning, 30(7), 757–779.\nEspedal, B. (2017). Understanding how balancing autonomy and power might occur in leading organizational change. European Management Journal, 35, 155–163.\nFowler, S. (2014). What Maslow’s hierarchy won’t tell you about motivation. Harvard Business Review, 92(11).\nGrewal, D., Roggeveen, A., Compeau, L., & Levy, M. (2012). Retail value-based pricing strategies: new times, new technologies, new customers. Journal of Retailing, 88(1), 1–6.\nHamilton, R., & Chernev, A. (2013). Low prices are just the beginning: price image in retail management. Journal of Marketing, 77, 11), 1–11),20.\nHenssen, B., Voordeckers, W., Lambrechts, F., & Koiranen, M. (2014). The CEO autonomy–stewardship behavior relationship in family firms: the mediating role of psychological ownership. Journal of Family Business Strategy, 5, 312–322.\nJaworski, B.J., & Kohli, A.K. (1993). Market orientation: antecedents and consequences. Journal of Marketing, 57(3), 53–70.\nJohanssen, M., Keränen, J., Hinterhuber, L., & Andersson, L. (2015). Value assessment and pricing capabilities—how to profit from value. Journal of Revenue and Pricing Management, 14(3), 178–197.\nKakar, A. K. (2018). 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Harvard Business Review, 95 (1).\nMarquet, D. (2015). 6 myths about empowering employees. Harvard Business Review, 93.\nMeyer, J., & Shankar, V. (2016). Pricing strategies for hybrid bundles: analytical model and insights. Journal of Retailing, 92, 133–146.\nMorgan, N., Katsikeas, C., & Vorhies, D. (2012). Export marketing strategy implementation, export marketing capabilities, and export venture performance. Journal of the Academic Marketing Science, 40, 271–289.\nMurray, J., Gao, G., & Kotabe, M. (2011). Market orientation and performance of export ventures: the process through marketing capabilities and competitive advantage. Journal of Academic Marketing Science, 39, 252–369.\nPratono, A. H. (2016). Strategic orientation and information technological turbulence: contingency perspective in SMEs. Business Process Management Journal, 22(2), 368–382.\nPratono, A. H., & Mahmood, R. (2015). Entrepreneurial orientation and firm performance: how can micro, small and medium-sized enterprises survive environmental turbulence? Pacific Science Review B: Humanities and Social Sciences, 1(2), 85–91.\nRajesh, R. (2017). Technological capabilities and supply chain resilience of firms: a relational analysis using Total Interpretive Structural Modeling (TISM). Technological Forecasting and Social Change, 118, 161–169.\nRay, G., Muhanna, W. A., & Barney, J. B. (2007). Competing with IT: The role of shared IT-business understanding. Communication of the ACM, 50(12), 87–91.\nSchilke, O. (2014). On the contingent value of dynamic capabilities for competitive advantage: the nonlinear moderating effect of environmental dynamism. Strategic Management Journal, 35, 179–203.\nWilliam, C., Colovic, A., & Zhu, J. (2017). Integration-responsiveness, local hires and subsidiary performance amidst turbulence: insights from a survey of Chinese subsidiaries. Journal of World Business, 52, 842–853.\nWu, L., Liu, H., & Zhang, J. (2017). Bricolage effects on new-product development speed and creativity: the moderating role of technological turbulence. Journal of Business Research, 70, 127–135.\nYeo, C. S., Venugopal, S., Chu, X., & Buyya, R. (2010). Autonomic metered pricing for a utility computing service. Future Generation Computer Systems, 26, 1368–1380.\nZhang, J., & Duan, Y. (2010) The impact of different types of market orientation on product innovation performance: Evidence from Chinese manufacturers. Management Decision, 48(6), 849–867.\nZhu, H., Xia, J., & Makino, S. (2015). How do high-technology firms create value in international M&A? Integration, autonomy, and cross-border contingencies. Journal of World Business, 50, 718–728.",{"EN":1610},"This study aims to determine the impact of technological turbulence on the relationship between autonomy, pricing capability, and firm performance. The structural equation model was proposed to investigating the complex relationship of the observed variables. Hence, this study carried out a survey that involved small and medium-sized enterprises (SMEs) in Indonesia context. The results indicate that the pricing capability provides mediating effect on the relationship between autonomy and firm performance. Under moderate technological turbulence, the firms with high autonomy level achieve high performance by enhancing pricing capability. On the other hand, the firms with strong entrepreneurial autonomy suffer under high technological turbulence. This study extends the works on the entrepreneurial behaviors by answering the question on how technological turbulence influences the initiative to promote entrepreneurial autonomy.",{"EN":1612},"Does Entrepreneurial Autonomy Foster SME Growth Under Technological Turbulence? 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