Michelle Ng

All Publications

• Affective Sensitivity to Air Pollution (ASAP): Person-specific associations between daily air pollution and affective states. PloS one Ng, M., Gerstorf, D., Conroy, D. E., Pincus, A. L., Ram, N. 2024; 19 (8): e0307430

  Abstract

  Individuals' sensitivity to climate hazards is a central component of their vulnerability to climate change. In this paper, we introduce and outline the utility of a new intraindividual variability construct, affective sensitivity to air pollution (ASAP)-defined as the extent to which an individual's affective states fluctuate in accordance with daily changes in air quality. As such, ASAP pushes beyond examination of differences in individuals' exposures to air pollution to examination of differences in individuals' sensitivities to air pollution. Building on known associations between air pollution exposure and adverse mental health outcomes, we empirically illustrate how application of Bayesian multilevel models to intensive repeated measures data obtained in an experience sampling study (N = 150) over one year can be used to examine whether and how individuals' daily affective states fluctuate with the daily concentrations of outdoor air pollution in their county. Results indicate construct viability, as we found substantial interindividual differences in ASAP for both affect arousal and affect valence. This suggests that repeated measures of individuals' day-to-day affect provides a new way of measuring their sensitivity to climate change. In addition to contributing to discourse around climate vulnerability, the intraindividual variability construct and methodology proposed here can help better integrate affect and mental health in climate adaptation policies, plans, and programs.

  View details for DOI 10.1371/journal.pone.0307430

  View details for PubMedID 39110667

  View details for PubMedCentralID PMC11305556

• Climate impacts of digital use supply chains Environmental Research: Climate Shi, L., Brandt, A., Iancu, D., Mach, K. J., Field, C., Cho, M., Ng, M., Chey, K., Ram, N., Robinson, T., Reeves, B. 2024; 3 (1)

  View details for DOI 10.1088/2752-5295/ad22eb

• Embracing climate emotions to advance higher education Nature Climate Change Pellitier, P., Ng, M., Castaneda, S., Moser, S., Wray, B. 2023

  View details for DOI 10.1038/s41558-023-01838-7

• Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. Journal of affective disorders Torous, J., Lipschitz, J., Ng, M., Firth, J. 2020; 263: 413-419

  Abstract

  Low engagement and attrition from app interventions is an increasingly recognized challenge for interpreting and translating the findings from digital health research. Focusing on randomized controlled trials (RCTs) of smartphone apps for depressive symptoms, we aimed to establish overall dropout rates, and how this differed between different types of apps.A systematic review of RCTs of apps targeting depressive symptoms in adults was conducted in May 2019. Random-effects meta-analysis were applied to calculate the pooled dropout rates in intervention and control conditions. Trim-and-fill analyses were used to adjust estimates after accounting for publication bias.The systematic search retrieved 2,326 results. 18 independent studies were eligible for inclusion, using data from 3,336 participants randomized to either smartphone interventions for depression (n = 1,786) or control conditions (n = 1,550). The pooled dropout rate was 26.2%. This increased to 47.8% when adjusting for publication bias. Study retention rates did not differ between depression vs. placebo apps, clinically-diagnosed vs. self-reported depression, paid vs. unpaid assessments, CBT vs. non-CBT apps, or mindfulness vs. non-mindfulness app studies. Dropout rates were higher in studies with large samples, but lower in studies offering human feedback and in-app mood monitoring.High dropout rates present a threat to the validity of RCTs of mental health apps. Strategies to improve retention may include providing human feedback, and enabling in-app mood monitoring. However, it critical to consider bias when interpreting results of apps for depressive symptoms, especially given the strong indication of publication bias, and the higher attrition in larger studies.

  View details for DOI 10.1016/j.jad.2019.11.167

  View details for PubMedID 31969272

• User Engagement in Mental Health Apps: A Review of Measurement, Reporting, and Validity. Psychiatric services (Washington, D.C.) Ng, M. M., Firth, J., Minen, M., Torous, J. 2019; 70 (7): 538-544

  Abstract

  Despite the potential benefits of mobile mental health apps, real-world results indicate engagement issues because of low uptake and sustained use. This review examined how studies have measured and reported on user engagement indicators (UEIs) for mental health apps.A systematic review of multiple databases was performed in July 2018 for studies of mental health apps for depression, bipolar disorder, schizophrenia, and anxiety that reported on UEIs, namely usability, user satisfaction, acceptability, and feasibility. The subjective and objective criteria used to assess UEIs, among other data, were extracted from each study.Of 925 results, 40 studies were eligible. Every study reported positive results for the usability, satisfaction, acceptability, or feasibility of the app. Of the 40 studies, 36 (90%) employed 371 indistinct subjective criteria that were assessed with surveys, interviews, or both, and 23 studies used custom subjective scales, rather than preexisting standardized assessment tools. A total of 25 studies (63%) used objective criteria-with 71 indistinct measures. No two studies used the same combination of subjective or objective criteria to assess UEIs of the app.The high heterogeneity and use of custom criteria to assess mental health apps in terms of usability, user satisfaction, acceptability, or feasibility present a challenge for understanding real-world low uptake of these apps. Every study reviewed claimed that UEIs for the app were rated highly, which suggests a need for the field to focus on engagement by creating reporting standards and more carefully considering claims.

  View details for DOI 10.1176/appi.ps.201800519

  View details for PubMedID 30914003

  View details for PubMedCentralID PMC6839109

• CommunityCrit: Inviting the Public to Improve and Evaluate Urban Design Ideas through Micro-Activities Mahyar, N., James, M. R., Ng, M. M., Wu, R. A., Dow, S. P., ACM ASSOC COMPUTING MACHINERY. 2018

  View details for DOI 10.1145/3173574.3173769

  View details for Web of Science ID 000509673102039